Journal of Medical Internet Research - American Medical Association Shares Framework to Address the Escalating Risk of Physician Deepfakes

American Medical Association Shares Framework to Address the Escalating Risk of Physician Deepfakes

American Medical Association Shares Framework to Address the Escalating Risk of Physician Deepfakes

Authors of this article:

Shalini Kathuria Narang, JMIR Correspondent

As AI becomes more sophisticated, new risks are emerging. In this News and Perspectives article, JMIR Correspondent Shalini Kathuria Narang reports on the American Medical Association’s response to the rising issue of physician deepfakes.

Key Takeaways:

• Deepfakes created to impersonate doctors, manipulate the public, and endorse unproven treatments pose threats to patients and the broader health care system.
• The American Medical Association has released a new policy framework to establish clear, enforceable protections for physicians against unauthorized AI-generated deepfakes.
• Some states’ legislatures in the United States have passed laws to discipline vendors where an AI chatbot is engaged in the practice of medicine or is impersonating a human engaged in the practice of medicine.

A deepfake is a video, photo, or audio recording that seems real but has been manipulated with AI. The underlying technology can replace faces, manipulate facial expressions, and synthesize speech, depicting humans appearing to say or do something that they have never said or done.

AI-generated deepfake “doctors” impersonating physicians garner millions of views on social media, misleading the public and endorsing unproven treatments. The content typically promotes products for their creators’ financial gain while exposing the viewers to scams that erode the patient-physician relationship, undermine confidence in evidence-based care, and put the public at risk of harm.

According to the factchecking organization Full Fact, hundreds of AI-generated deepfakes of real doctors and academics to promote health products with bogus endorsements are damaging the reputations of those they impersonate and could lead to people making decisions about their health based on fake claims.

“[The] mental health space is an area of big concern, including significant privacy concerns, more with some of the general purpose chatbots claiming to help support mental health. We know many, many, many individuals and patients are using these chatbots for support that can cross the line and be dangerous, as we’ve seen suicides and bad outcomes related to the use of these chatbots in certain ways,” says Shannon Curtis, JD, Senior Director of Policy Development for the American Medical Association (AMA) Center for Digital Health and AI.

She adds that the AMA is looking for solutions to begin addressing the issue, including transparency to help users understand that they’re not actually engaging with a licensed clinician.

“We want to see a prohibition on chatbots from claiming they’re a licensed professional, or that they’re providing equivalent services as a licensed professional,” says Curtis. “We have called for more action to update our regulatory structure... A call for new, updated, appropriate regulatory oversight structures that can help provide that clarity and consistency for consumers, for physicians, for the industry, about what needs to be regulated, and what does not. And hopefully, turning that into a more appropriate, risk based regulatory system that fits where AI is, and hopefully fits where it is going.”

As AI chatbots become more sophisticated, and more harms are realized, it is likely more states will create regulations and exercise enforcements.

New AMA Policy Framework

Responding to the escalating risk of AI deepfakes, and recognizing that existing privacy, employment, and intellectual property laws do not adequately address AI deepfake risks in clinical contexts, the AMA Center for Digital Health and AI has created a policy framework to modernize physician identity protections and close legal gaps to uphold patient safety, professional integrity, and public trust.

The framework is built on 7 policy principles:

• Physician identity as a protected right: A physician’s name, image, likeness, voice, and digital replicas are protected interests and should not be used beyond the scope of the clinician’s consent.
• Prohibition on deceptive medical impersonation: AI-generated or altered content falsely conveying a physician’s endorsement, authorship, or medical judgment likely to mislead in a health-related decision must be prohibited.
• Informed, opt-in, and revocable consent: Use of a physician’s identity in AI-generated or manipulated content requires affirmative, informed, opt-in consent.
• Mandatory transparency and labeling: AI-generated or altered content depicting a physician must be clearly labeled. Patients interacting with an AI-generated health professional must be alerted before the interaction.
• Shared responsibility to prevent impersonation: All participants—platforms, hospitals, health systems, and AI vendors—share responsibility for preventing identity misuse.
• Enforcement and practical remedies: Processes must be in place to allow physicians to document, escalate, and address identity misuse. Institutions and platforms must facilitate investigation and escalation.
• Minimizing administrative burden: Protecting physician identity should be a default that doesn’t place any undue burden on the physician.

“AI deepfakes that impersonate physicians are not just scams—they are a public health and safety crisis,” said AMA CEO John Whyte via a statement. “When bad actors exploit a doctor’s identity, they undermine patient trust and can steer people toward harmful, unproven care. We need strong action by federal and state lawmakers to protect physicians’ identities, ensure transparency, and stop this fraud. Safeguarding professional integrity is essential to preserving trust and delivering high-quality care in a rapidly evolving digital landscape.”

The new AMA framework aims to guide how the organization works with government officials and industry partners to stop AI-generated deepfakes of physicians. The AMA is eager to collaborate with lawmakers, regulators, and industry to protect patients and doctors from these risks.

“We were seeing a lot of physicians having their names stolen. It’s turning up on things like academic papers, that they had no part of. Our framework seeks to address those issues by creating a prohibition and requiring affirmative, opt-in consent from the physician in question if their name, image likeness, voice, etc, is going to be used going forward,” says Curtis.

Enforcing Guidelines

While the framework currently functions as a set of guidelines, Curtis notes that the AMA intends for it to lead to enforceable standards.

“Via the policy framework, we are seeking to create statutory or legal obligations that would prohibit a third party from creating a digital replica or a deepfake that utilizes a person’s name, image, likeness, or voice in a nonconsensual way,” she says.

She emphasizes the importance of enforcement mechanisms like statutory or regulatory requirements on the platforms that end up hosting this content and enforcement by a government agency like the Federal Trade Commission for those bad actors that are creating the deepfakes and disseminating them.

“Data privacy is a huge issue that is sometimes not well understood by individuals. We’d like to see some more action to help protect patients’ personal health information,” says Curtis. The AMA is collaborating with other groups to support the notice-and-removal obligations in the Take It Down Act and a growing coalition in support of the enactment of the NO FAKES Act.

Regulating medical practice typically falls under the jurisdiction of state medical boards in the United States. In addition to a recent landmark lawsuit filed by the Governor of Pennsylvania against Character.AI, some states’ legislatures have passed laws—for example, AB 489 in California, HB 2748 in Oregon, and the Conversational AI Safety Act in Nebraska—to discipline vendors where an AI chatbot is engaged in the practice of medicine or is impersonating a human medical professional.

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Journal of Medical Internet Research - American Medical Association Shares Framework to Address the Escalating Risk of Physician Deepfakes

Connecticut doctors caution against microwaving fidget toys due to risk of burns

 

Connecticut doctors caution against microwaving fidget toys due to the risk of burns

Health officials are warning about children burning themselves after microwaving gel-filled fidget toys. 

A new trend circulating online is prompting children to microwave squishy, gel-filled toys, which can be found and purchased at many stores nationwide. 

Doctors in Connecticut said they have seen a case or two of burns in children as a result, even causing a second-degree burn in one instance.

The doctors said these types of burns are a little different because the sticky substance inside sticks to the skin and will continue burning until you get it off. Their message — just don’t heat them up.

“Not putting things in the microwave that weren’t designed to be microwaved, that’s not the way the toy was designed to be used,” Dr. Alisa Savetamal, the medical director of The Connecticut Burn Center, said. “We have no idea how hot it gets. Be aware of these TikTok trends; they cannot be as fun as you think.”

If a child does suffer a burn from a toy like this, or even something else, the best immediate remedy is to run the skin under cool water. While some small burns can be managed at home, if you’re concerned, go to the doctor, as this type of injury can leave a scar.

Medicaid work requirements challenged by coalition of 26 states

Medicaid work requirements put into place by the President Donald Trump-backed One Big Beautiful Bill Act are being challenged in federal court by a coalition of states, seeking to block a Final Rule from the Centers for Medicare & Medicaid Services that outlined how they would be implemented.

The lawsuit, led by California and Massachusetts, is joined by Arizona, Colorado, Connecticut, Delaware, District of Columbia, Hawaii, Illinois, Kentucky, Maine, Maryland, Michigan, Minnesota, Nevada, New Mexico, New Jersey, New York, North Carolina, Oregon, Pennsylvania, Rhode Island, Vermont, Virginia, Washington and Wisconsin, representing both “blue” and “red” states, showing that the work requirements have some bipartisan opposition in state governments.

In a press release, Massachusetts Attorney General Andrea Joy Campbell said the interim final rule from CMS—published on June 3—is failing to protect the list of exclusions to the work requirements that Congress put in place to “ensure that people with serious illnesses and disabilities do not lose coverage or face interruptions in care.”

According to Campbell, speaking on behalf of the plaintiffs, CMS’s rule is an “abrupt change” that, if allowed to stand, would “make it significantly harder for vulnerable individuals to qualify for exclusions from the Medicaid work requirements and harder to maintain Medicaid coverage.” 

The sticking point is how the term “medically frail” is defined—a key category that would allow an individual access to Medicaid regardless of their status as an employee or a student.   Being medically frail generally refers to having a serious or chronic physical, mental, or medical condition that makes it hard to sustain steady work or perform normal daily activities without significant help. [1]

Under federal and state policies (such as recent Medicaid work requirement exemptions), the term specifically includes individuals who: [1, 2]

• Are blind or have a disability as defined by the Social Security Administration.
• Have a substance use disorder (SUD).
• Suffer from a disabling mental health condition.
• Have a physical, intellectual, or developmental disability that significantly impairs their ability to perform Activities of Daily Living (ADLs).
• Live with serious or complex medical conditions, such as cancer or HIV. [1, 2]

Could you tell me what specific program or situation (e.g., Medicaid, Medicare, or a life insurance policy) you are checking this for? I can help you find the exact guidelines and exemption forms that apply to you.

CMS’s requirement would force people who are in need of healthcare services to find specialty jobs to accommodate them, where none may exist, the plaintiffs argue. The states contend that the agency appears to be trying to ensure this exemption is effectively nullified.

“The Trump Administration’s attempt to impose new, burdensome requirements on Medicaid recipients threatens access to healthcare for our most vulnerable residents and families,” Campbell said in a statement. “Congress made clear that people with serious medical conditions should not lose coverage.”

“We are asking the court to block these unlawful provisions to protect Medicaid recipients and prevent needless strain on Massachusetts’ healthcare system.”

Burden of proof

As for the specifics of the legal challenge, the states are asking a court to force CMS to change the rule, contending that it violated the Administrative Procedure Act and bypassed Congress’s intent to add real safeguards for Americans to access safety net healthcare services. 

Further, the coalition says states will be left holding the bag, dealing with the fallout from a population with significant medical needs that can’t access Medicaid because of the overly strict federal mandates, particularly a reporting burden that effectively forces states to prove a citizen is “medically frail.”

The lawsuit has yet to be heard in front of a federal judge.

Medicaid work requirements challenged by coalition of 26 states

 

She Struggled To Get a Lifesaving Drug Even After Insurers Vowed To Help

By Samantha Liss

Jun 29, 2026

LADUE, Mo. — Over four consecutive days in January, Margaret Hvatum ran a 5K, a 10K, a half-marathon, and a full marathon. The 70-year-old covered a combined distance that’s nearly equivalent to running the length of Manhattan four times. 

By the end of the month, she was in a hospital bed.

Hvatum, a part-time computer science professor, has a weakened immune system due to a rare condition known as primary immunodeficiency, which makes it difficult for her body to fight infections. Prior to her 2005 diagnosis, she had four bouts of shingles, a painful rash caused by a virus.

For more than a decade, she relied on an expensive medicine to treat her chronic condition — and relied on her insurance to pay for it.

Then the denial letters came.

The Medical Service

To give her weakened immune system a boost, she relies on Hizentra, which is made up of antibodies collected from donated blood plasma.

At her home, near St. Louis, Hvatum can administer the complex medicine herself. She uses a large syringe to draw the medicine from a vial and loads the syringe into a plastic apparatus that looks like a toy Nerf gun. She cranks a blue plastic dial that triggers a steady drip of the medicine, and it snakes through plastic tubing until it enters her leg through a needle.

The Bill

$8,141.94: The full charges for a 28-day supply of Hizentra without insurance coverage.

After her Medicare Advantage plan through Humana denied payment for the drug in January, she missed several weekly doses.

The Billing Problem: Prior Authorization

Hvatum got tangled up in the controversial process known as prior authorization, which often requires patients or their medical team to get an insurance company’s approval before obtaining medicines or treatment. 

At the start of the year, after Hvatum switched Medicare Advantage plans, she received a letter saying that Humana, her new carrier, had denied her “prior authorization prescription request” for Hizentra. The authorization from her previous insurer didn’t carry over. 

Without the medicine, Hvatum developed a urinary tract infection that sent her to the emergency room on Jan. 30. Though it is a common infection, her doctor advised her to go there because people with her condition can get sick and deteriorate quickly, she said. 

That ER visit turned into an overnight hospital stay. That turned into hospital charges of more than $18,000, and again her insurance denied payment, saying this time that she wasn’t sick enough to require hospital care.

Hvatum’s experience with prior authorization is not unique.

Medicare Advantage plans reviewed nearly 53 million prior authorization requests in 2024, according to KFF. That’s equivalent to nearly two reviews for every person enrolled in the program.

It’s common for Medicare Advantage plans to deny payment for care — which helps them make a profit, said Carrie Graham, director of the Medicare Policy Initiative at Georgetown University’s Center on Health Insurance Reforms.

The government pays a monthly sum to Medicare Advantage insurers to cover care for each member. “They make a profit if the care that person receives in that year is less than the amount they receive,” Graham said.

More than half of eligible Medicare beneficiaries choose Medicare Advantage insurance coverage. In 2026, roughly 35 million selected one of these private policies offered by insurance companies.

Humana is a dominant player in the space. Nearly half of all Medicare Advantage enrollees nationwide are covered by UnitedHealth Group or Humana, according to KFF.

The killing of UnitedHealthcare CEO Brian Thompson prompted renewed scrutiny of prior authorization. Last summer, months after his death, the nation’s largest insurers, including Humana, signed a pledge that outlined a handful of commitments to ease the burden on patients.

For example, insurers vowed to reduce the number of services that would require prior authorization approval. They also promised to reduce delays by honoring existing prior authorizations for a 90-day period when patients switched plans.

That’s not what happened in Hvatum’s case.

Humana said this pledge to honor existing approvals comes with limitations. “These commitments are for medical services only and do not apply to prescription medications,” spokesperson Mark Taylor said.  

Humana declined to comment on the specifics of Hvatum’s case, even though she agreed to waive her privacy rights, giving the insurer permission to comment.

While acknowledging that the prior authorization process can be deeply frustrating for patients, Humana said it “builds important checks and balances into the healthcare system by verifying that treatments and care delivery are in the best interest of patient safety and quality of care, while safeguarding taxpayer dollars.”

In July 2025, Humana said it would remove one-third of prior authorization requirements for outpatient services.

“We are committed to making the process faster and more seamless for patients and providers,” Humana said in a statement Taylor provided to KFF Health News.

The Resolution

Hvatum appealed, and Humana in late January reversed its initial payment denial for Hizentra, enabling her to afford her medicine again.

But the approval came with a catch: It expires at the end of the year, after which she would need to obtain approval all over again.

Hvatum has since switched to a different drug — and she might not stick around for any more medical-bill fights like this one. She and her husband are considering a move to Norway, a place with universal healthcare. He is a citizen there, which could give her a path to public health coverage.

The industry’s promises to change are too little, too late for Hvatum. 

By her account, she has done her part. Running is her outlet, maybe an obsession, and it keeps her healthy. Scores of medals and trophies are tucked about her home. Some sit on a white wicker end table, next to family photos, candles, and framed St. Louis Cardinals memorabilia. Above a large bay window in the kitchen, medals hang from ribbons of all colors, made to look almost like custom window drapery.

“I have done everything I possibly can to be healthy,” Hvatum said, sitting at her dining room table in her running gear. Her printed T-shirt read, “If found on ground, please drag across the finish line.”

The Takeaway

Data show patients should appeal prior authorizations because those who do often have their denials reversed, Graham said. In fact, 81% of Medicare Advantage appeals were partially or fully overturned in 2024, according to KFF.

Relatively few people appeal, because “it’s an exhausting process,” Graham said. It puts the onus on patients — and doctors get frustrated, too.

It’s not just Medicare Advantage plans that subject enrollees to prior authorization approvals. It’s prevalent in other types of coverage, and it has prompted blowback from the public. Graham believes the public outcry instigated the industry’s pledge to change.

Hvatum is well-versed in filing appeals. She submitted another appeal to Humana after the insurer denied payment for her January hospital stay. Humana again reversed its denial of payment in her case.

Hvatum blames Humana for her January trip to the hospital. Had Humana approved her Hizentra, she said, she could have avoided hospital care altogether.

In March, she had a stroke. Humana denied coverage of that hospital stay, too.

Humana determined that it was not reasonable for the physician who admitted Hvatum to think she would need to stay at least two nights, the threshold for approval. “You had a small stroke,” Humana’s denial letter stated.

Hvatum noted the letter was dated March 25, two days after she was hospitalized. Humana reversed its denial two weeks after Hvatum appealed.

“They love to send you the denials fast,” Hvatum said. “Approvals take longer.”

Bill of the Month is a crowdsourced investigation by KFF Health News and The Washington Post’s Well+Being that dissects and explains medical bills. Since 2018, this series has helped many patients and readers get their medical bills reduced, and it has been cited in statehouses, at the U.S. Capitol, and at the White House. Do you have a confusing or outrageous medical bill you want to share? Tell us about it!

KFF Health News is a national newsroom that produces in-depth journalism about health issues and is one of the core operating programs at KFF—an independent source of health policy research, polling, and journalism. Learn more about KFF.

This article first appeared on KFF Health News and is republished here under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Signs of Early Dementia

 When most people think about early dementia warning signs, they think about forgetting names or getting lost. But researchers say the sign that appears earliest and gets missed most consistently is something almost nobody is watching for.

It is a loss of SMELL.

Specifically, the gradual inability to detect or identify familiar odors like coffee, flowers, and cleaning products appears years before any memory symptom surfaces.
A landmark study from the Rush Memory and Aging Project found that older adults who scored in the bottom 10% on smell identification tests were more than twice as likely to develop Alzheimer's disease over the following years. The reason is that the olfactory bulb, the brain's smell processing center, is one of the first regions where amyloid plaques accumulate in Alzheimer's disease. It is essentially a window into the brain's earliest pathological changes, visible years before cognitive symptoms emerge.
A simple smell test called the University of Pennsylvania Smell Identification Test is available through neurologists and some primary care offices. It takes 15 minutes. It is not routinely offered. Ask for it by name.

UPSIT (University of Pennsylvania Smell Identification Test): A widely used 40-item, multiple-choice scratch-and-sniff test considered a gold standard in the United States.

Other Olfactory Tests

Other readily observable changes are

Micrographia (smaller handwriting

Slowness of gait

Share this with someone who keeps saying their aging parent seems a little off but cannot explain why. ❤️

Complete Article and Video

Medical device industry continues to turn to AI | MedTech Dive

More medical device companies are integrating artificial intelligence into their products as the technology advances.

Imaging machines now use deep learning to speed up scans and flag potential lesions for radiologists. AI is also used in wearable devices to detect heart arrhythmias and in software systems to predict the risk of sepsis in hospitalized patients. 

As the proliferation of AI in the medtech industry continues, questions remain about the efficacy of these technologies, how they should be regulated and how to mitigate the risk of bias when used in patient care. 

How 4 medtech CEOs are using AI

At AdvaMed’s The MedTech Conference, executives said they’re incorporating AI in more devices, but figuring out how to use the technology internally is challenging.

By: Elise Reuter • Published Oct. 7, 2025

SAN DIEGO — Medtech executives are incorporating artificial intelligence into medical devices, but they are also wading into using the technology for administrative tasks. 

At AdvaMed’s The MedTech Conference, company leaders said they expect to incorporate AI into more of their devices. With the recent rise of generative AI, companies are also considering the technology for internal tools, but progress has been slower.

Here’s how four medtech executives are using AI today: 

Stryker CEO Kevin Lobo

Lobo said every one of Stryker’s businesses has a digital or AI component. He also expects that Stryker will have a digital division in the future, following the company’s acquisitions of Vocera Communications and Care.ai.

“Five years ago, I would have never thought I’d be buying an AI company,” Lobo said.

With Vocera, Stryker has a technology that provides badge alerts to healthcare workers based on what’s happening in a patient’s room. For example, if a patient is lowering a guardrail to leave their bed, it can send an alert to prevent falls.

Stryker is also developing AI technologies in surgery. The company has a system, called Blueprint, that advises surgeons on the type of implant they should use in an operation and provides a surgery plan.

Projects that use innovation to solve a problem for Stryker’s customers are easy to prioritize, Lobo said, adding that teams “have no trouble finding the money” for these projects.

Figuring out how to use AI for internal productivity is more difficult.

“Frankly, we’re a little bit behind where I’d like to be,” he said, noting that the company is focusing on areas such as customer service and regulatory work. 

Insulet CEO Ashley McEvoy

McEvoy, who became CEO of Insulet in April 2025, said the diabetes technology company has used OpenAI’s foundation models for customer care and retention. Insulet uses the technology to provide customer care agents access to company knowledge, which can help with call wait times. 

Looking to the future, McEvoy hopes to use Insulet’s data in a precision medicine play to build more personalized algorithms for the company’s insulin pump users. 

From a culture perspective, McEvoy said she is working with company leaders to “embrace the good parts of [AI] and not be naive to some of the darker sides,” but still have the freedom to experiment.

Insulet CEO Ashley McEvoy speaks at The MedTech Conference.

Elise Reuter/MedTech Dive, data from MedTech Dive

 

Hologic CEO Stephen MacMillan

MacMillan said AI has been helpful with the rise of 3D mammography, which creates more images than 2D mammograms. Looking through so many images can be fatiguing for radiologists. The company uses machine learning to distill the process down to “go look at slide 3 in the upper left quadrant instead of looking at hundreds of slides,” MacMillan said. 

The company has started using AI in its breast imaging segment, but plans to roll it out to the rest of its businesses. For example, Hologic has developed a newer tool to support pap smears, which are still often done by cytologists looking at individual slides through microscopes. The company has digitized the process and uses machine learning to flag objects of interest for cervical cancer. Hologic received the FDA’s de novo authorization for the digital cytology system in 2024. 

Olympus Chief Strategy Officer Gabriela Kaynor

Four years ago, Olympus started focusing on investing in its data and AI capabilities, but more geared toward the company’s medtech products, Kaynor said. That has culminated in a recent product launch for AI to support colorectal polyp detection, as part of a broader platform to use AI in endoscopy. 

In the past two years, Kaynor said, Olympus has explored AI more for enterprise productivity. For example, Olympus built an internal AI tool to help with language translation, which can be a friction point. 

Olympus is headquartered in Tokyo, and work is done in Japanese, English and German. Being able to translate data — which might be sensitive — without it leaving the company was a good use case for the technology, Kaynor said. Olympus has been piloting the tool, and the company is getting ready to launch it internally. 

“This has been something that I think has reached, really, every corner of our company,” Kaynor said.

Article top image credit: Elise Reuter/MedTech Dive, data from MedTech Dive

Nvidia’s David Niewolny on the future of AI in medical devices

Nvidia, which is already working with J&J and Medtronic, plans to partner with medtech companies to build platforms for AI-enabled robotics, imaging and other features.

By: Elise Reuter • Published June 2, 2025

As more medical device companies incorporate artificial intelligence, chip designer Nvidia is playing a central role. The company has struck partnerships with top medtech firms including Medtronic, Johnson & Johnson, GE HealthCare and Philips.

The uses span a breadth of technologies. In imaging, Nvidia has partnered with GE HealthCare around autonomous X-ray and ultrasound solutions, and is working with Philips to develop foundation models, a type of model that can be used for a wide variety of tasks, for MRI machines. In robotics, J&J’s Monarch platform for bronchoscopy uses Nvidia’s computing platform. Nvidia also debuted a new developer framework for healthcare robotics in March 2025, called Isaac for Healthcare. The system features three computers to generate synthetic data to simulate workflows, create virtual environments where robots can safely learn skills, and a platform to deploy applications and for real-time sensor processing. 

MedTech Dive spoke with David Niewolny, director of business development for healthcare and medical at Nvidia, about the company’s partnerships and the future of AI in medical devices.

This interview has been edited for length and clarity.

MEDTECH DIVE: What’s the current state of AI in medtech? 

DAVID NIEWOLNY: In the last 18 months, we’ve seen this really fast progression in terms of healthcare and medtech adopting generative AI. That’s starting the idea of creating — drafting clinical notes, generating synthetic data for training. Devices are now looking at how can they begin bringing agentic AI into these applications. You’re seeing digital agents being an assistant to the healthcare provider or the patient with automating workflows, driving more context-aware support for clinicians. 

Then you get to where we see the future. Where a lot of the AI and innovation is happening is in the idea of physical AI. And that brings us into this role of robotics. The easy one to think of is surgical AI. But there’s a huge number of applications. One specific use case that I talked about in Taiwan [at GTC Taipei] is with some of these more operational robotics. Think of a nurse assistant in terms of delivering medication, bringing different supplies around a hospital, making sure different areas of the hospital are stocked.

You recently announced a partnership with GE HealthCare around autonomous imaging. How does that work? 

That was around completely transforming the way that you would look at doing medical imaging in the future. We took two initial use cases, one being the idea of an autonomous X-ray. Think of a future world where you no longer have the X-ray tech. You now have a digital agent that’s essentially checking you in. You walk into a room where there’s another robot, it could be a digital agent, that’s providing you with all of the guidance for where to stand, when to hold your breath and how to position yourself. You stand in one spot, and then the actual machine positions itself. 

You can also look at some of the generative AI applications, where it can hand a doctor a full report on everything that it saw in terms of its clinical findings.

In that particular case, now you’re expanding the access to care because you essentially have these fully autonomous systems that are doing medical imaging. 

X-ray is one that we announced, and the other one is around ultrasound. In each one of these cases, GE HealthCare is working with us and collaborating on a methodology and tools to build these robotic systems. 

What opportunities does Nvidia see in AI in medical devices?

Everything is about building an ecosystem. You look at all of the great work that we can do from accelerating a lot of these applications with AI and now robotics, going from Nvidia direct to a healthcare provider, there’s just too big of a gap. They don’t have the developers in-house to begin building this. 

So, then you work backwards in that ecosystem, and you realize it’s the medtech companies that are building out all of these devices and solutions. What we’re looking at doing is, how do we bring all of those components of the ecosystem together, building on a common platform? Computers were not mainstream until Windows opened the door for this huge influx of software. 

A lot of this learning we took from another industry: automotive. We essentially needed to create a fully simulated environment, train on that simulated data, take those algorithms and move them down to the edge.

We took those learnings and said, “What other areas are ripe for disruption?” Medtech, specifically, has the most to benefit from this opportunity of having a common platform. But at the same time, it had a big hurdle to jump over. There wasn’t any single company in that ecosystem, as we saw it, that could essentially build out that platform.

I’m hearing more people talk about Agentic AI, a type of AI that can perform autonomous tasks. Why are medtech companies interested in this technology?

Agentic AI has a whole number of applications. A partner of ours, Abridge, leveraged a lot of our technology to do clinical documentation. They’re integrating with major EHRs, and they’re continuing to get more and more hospital users. 

You also have some of these agents actually working right alongside a surgeon, where now you have an assistant in the room, where you can begin asking questions, pulling up the patient’s medical records, adjusting some of the devices in the room. 

One of our partners, Moon Surgical, actually downloaded their entire instructions for use manual into an agent that a doctor or surgeon can reference for things like setup. Instead of referencing a 1,000-page manual, you can just ask the robot where to be set up, how to be set up and what are the best practices?

Have you faced concerns from clinicians about AI taking their jobs?

Yes, people do get concerned. The key piece is, in almost every one of these cases, we’re augmenting the team members that are already there. There’s a shortage in place. This is actually improving care, as opposed to the narrative around taking people’s jobs. We take a lot of those workloads that the staff sees as either busy work or mundane, and augment them.

There’s always going to be a surgeon involved here, but we can do sub-task automation and actually make some of those tasks easier for a surgeon.

Article top image credit: Permission granted by Nvidia

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Is your risk-based monitoring strategy ready for the era of AI and sensors?

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By RQM+

Risk-based monitoring (RBM) was designed for a different era of clinical trials. The model of periodic site visits, manual source data verification, and centralized trend analysis assumed that the most important information would arrive in batches, to be reviewed after the fact. That assumption no longer holds.

Connected devices, remote sensors, and decentralized trial designs have changed the data environment. Sponsors now receive continuous streams of real-world performance data instead of periodic snapshots. The question facing clinical operations executives is whether their RBM infrastructure is capable of using it.

From snapshots to continuous streams

The shift matters because the risk profile of modern trials has changed in kind, not just degree. In hybrid and decentralized clinical trial (DCT) designs, risk moves away from site-level administration and toward patient device usage and remote data submissions. Fixed monitoring schedules designed around pre-set site contacts cannot adequately address the deviations that show up in real-time data between visits.

Real-time access allows sponsors and CRAs to detect irregular patterns like missed submissions, incorrect device usage, and anomalous sensor readings as they occur, allowing them to direct intervention resources precisely where they are needed. Under both FDA guidance and EU MDR’s increasingly stringent post-market clinical follow-up (PMCF) requirements, that kind of continuous, adaptive oversight is no longer optional.¹

AI as a force multiplier — with limits

AI and machine learning tools offer the scalable oversight necessary to process high-volume continuous data streams and flag signals that would be normally be lost in manual review. Analysis suggests that AI-enabled monitoring has strong potential to redirect resources toward high-performing centers and accelerate site-level decision-making.² However, AI can make mistakes (e.g., false positives), so the most defensible approach is human-guided automation: AI detects irregularities and potential safety issues, but no action is taken without clinical expert confirmation.

Governance is the real constraint

For most organizations, the barrier to modernizing RBM is governance. AI tools require high-quality, structured data to function reliably. Teams that lack clear protocols for human oversight, defined accountability at the investigator level, and infrastructure to handle continuous data streams will find that adding technology compounds the problem rather than solving it.

Before live deployment, leading sponsors use three approaches to stress-test their frameworks without exposing sensitive patient data:³

• Synthetic data modeling — simulated datasets allow teams to test monitoring strategies and filtering algorithms before live integration
• Data filtering — separating signal from noise in real time ensures monitoring efforts focus on meaningful deviations, not data volume
• In silico optimization — computer modeling predicts anatomical responses and adverse event timing, helping sponsors refine inclusion criteria

The executive takeaway

RBM is no longer a clinical operations function. It is a core component of life cycle management, PMCF strategy, and regulatory compliance. Organizations not treating it as such are carrying risk they may not see until it reveals itself in a regulatory finding or a trial that cannot generate defensible evidence.

Modernizing RBM means addressing four organizational realities:

• Study oversight has evolved — your infrastructure needs to handle modern hybrid and decentralized models, not just periodic site visits
• Manual review is a signal for change — extra manual steps or bypassed remote data opportunities suggest your data management strategy needs a refresh
• Governance is nonnegotiable — AI and ML drive efficiency, but clinical context and data quality are the investigators’ responsibility
• Partnership matters more than software — you need partners who understand MedTech device complexity, not generic platforms built for pharma

References

1 FDA Guidance. (2024). Digital Health Technologies for Remote Data Acquisition in Clinical Investigations.
2 Applied Clinical Trials. (2025). Modernizing Clinical Oversight: The Shift to Adaptive Monitoring.
3 Journal of Clinical Innovation. (2025). The Role of In Silico Modeling in Modern Trial Design.

Article top image credit: PeopleImages. Retrieved from Shutterstock.

FDA exempts more wearable, AI features from oversight

In a pair of guidance documents, the regulator clarified the types of wellness features and clinical decision support tools that don’t fall under medical device oversight.

By: Elise Reuter • Published Jan. 8, 2026

The Food and Drug Administration released two final guidance documents in January 2026 that would loosen regulations for certain types of wellness and software products. 

FDA Commissioner Marty Makary announced the changes at the Consumer Electronics Showcase. Makary, in a video posted on X, said the changes would “promote more innovation with AI in medical devices.”

Wellness exemptions for blood pressure, blood glucose

The first guidance clarifies the FDA’s thinking on what constitutes a wellness device. It offers broader leeway to wearables that provide readings around heart rate, blood pressure and blood glucose, so long as they are intended solely for wellness purposes.

In examples provided in the guidance, the FDA said a wrist-worn wearable that tracks metrics including sleep, pulse rate and blood pressure would fall under a general wellness claim, provided the product has validated values for blood pressure.

The guidance appears to contradict a warning letter the FDA sent to wearable company Whoop in 2025 for rolling out a blood pressure feature without authorization. At the time, the agency said that blood pressure is inherently related to a medical diagnosis.

A spokesperson for Whoop applauded the new guidance in an emailed statement, saying it clarifies that Whoop can provide blood pressure insights and wellness metrics when designed for non-medical purposes. The spokesperson said the changes should “help resolve long-standing uncertainty about the boundary between providing wellness insights and medical diagnosis and treatment.”

Another example was for a wearable intended to provide blood glucose estimates to monitor nutritional impacts, and is explicitly contraindicated for use by people with diabetes and pre-diabetes. According to the guidance, this would fall under a general wellness claim, but would not count as a low-risk product if the device used microneedle technology to provide the estimates. 

In 2024, the FDA warned consumers not to use smart watches or smart rings that claim to measure blood sugar without piercing the skin. 

“In the past, the FDA has permitted some measurements like pulse rate and O2 saturation in some wellness products, but not others,” Makary said in a speech at CES. “It didn’t always make a lot of sense from the outside.”

Tom Hale, CEO of Oura, maker of a wearable ring that is working on a blood pressure feature, welcomed the changes in a LinkedIn post.

“As wearables continue to evolve, modern regulation that recognizes the difference between early awareness and medical diagnosis is critical,” Hale wrote.

Less regulation of clinical decision support software

In a separate guidance, the FDA unveiled significant changes to how it regulates clinical decision support tools. The biggest change is to a section describing how the FDA interprets whether software is providing recommendations to healthcare providers. Software that provides a sole medical recommendation can now be exempt from regulation. Under a previous guidance, it would have been considered a medical device. 

For example, according to the new guidance, software that predicts a patient’s risk of future cardiovascular events based on their weight, smoking status, blood pressure and lab tests would be exempt from FDA enforcement. However, if the same test was intended to predict the risk within 24 hours, or used genomic data, it would be considered a medical device.

Another example considers the use of software to summarize radiologists’ findings, a concept that firms are testing using generative artificial intelligence. A software function that analyzes a radiologist’s report to generate a summary with specific diagnostic recommendations would be exempt. However, if the software directly analyzed an image to create the report, it would still be regulated by the FDA. 

The guidance also spells out what information device makers must provide to clinicians so they can review the basis of the software’s suggestions. Software intended for critical, time-sensitive tasks would still be considered a device, and companies should provide a description of the underlying algorithm, validation and required input information, the FDA said.

The pair of guidance documents offers some insight into the Trump administration’s approach to AI. In past months, the administration has pushed for a deregulatory approach, but with few details. The Department of Health and Human Services issued a request for information to the healthcare industry in December 2025, asking for feedback on how the department can help speed adoption of AI.

Both documents were published without a public comment period, an approach the Trump administration has recently taken for major policy changes.

Article top image credit: Courtesy of Whoop

CDRH Director Tarver previews AI guidance at AAMI event

Michelle Tarver said the device center plans to finalize guidance on AI lifecycle management and provide some initial thoughts on generative AI following an advisory committee meeting.

By: Elise Reuter • Published April 22, 2026

Michelle Tarver, director of the Center for Devices and Radiological Health, provided an update on digital health and artificial intelligence policy at the Association for the Advancement of Medical Instrumentation’s neXus conference.

Tarver said the CDRH plans to issue final guidance on AI lifecycle management, and told attendees to watch for the center’s thinking following two advisory committee meetings on generative AI.

The Food and Drug Administration published draft guidance on AI lifecycle management in January 2025. The document outlines best practices to ensure AI-enabled devices are safe and effective, and how developers should address transparency and bias. 

All AI algorithms are required to be trained on data that reflects the intended use population and should be validated in the intended use population, Tarver said.

The draft guidance also addresses postmarket monitoring after an AI-enabled device is deployed in the real world, knowing that this technology can hallucinate, bias can come into play and models may drift, or become less accurate over time.

“All of that can impact the output that those technologies are generating and impact patient outcomes as a result,” Tarver said.

The FDA is currently looking at comments from the draft to issue a final guidance, Tarver said.

The CDRH director also addressed generative AI, a technology that can generate text, images, software code and other outputs.

The CDRH’s Digital Health Center of Excellence held two advisory committee meetings on the topic: one in 2024 on how the agency should regulate generative AI, and another in 2025 on digital mental health devices, including chatbots that may or may not be overseen by a clinician.

“We are taking all the feedback that we heard, and I encourage you to look toward the end of this year for some initial thoughts,” Tarver said.

The update provided clarity as the Trump administration has focused on AI adoption and deregulation, but with little information on what that means for healthcare.

In 2025, after President Donald Trump was sworn in for his second term, the CDRH issued just one final guidance related to AI, on predetermined change control plans. Meanwhile, the agency grappled with staff cuts, which affected experts in AI and digital health, although some employees were reinstated.

In 2026, the new year started off with two unannounced changes to digital health guidance documents that exempted some types of wellness features and clinical decision support tools from device regulations.

Article top image credit: Permission granted by AAMI

Medical device industry continues to turn to AI | MedTech Dive