Berci Meskó, MD, PhD

The Medical Futurist, Author of "Your Map to the Future", Global Keynote Speaker, and Futurist Researcher

[Berci Meskó, MD, PhD @Berci]

I cannot express my happiness and excitement about a book I’ve been working on for so long!

Here is Your Map to the Future: Learn How to Navigate and Shape What Lies Ahead!

In this book, I make science-based futures methods, that only experts including me at The Medical Futurist have been using for decades, accessible to everyone!

This heavily illustrated book describes how starting from the traps of short-term thinking and presentism, we can finally expand our time perspective and learn to observe and examine the future as we have been doing with the past.

Doing this is crucial in addressing today’s most pressing issues, from climate change to the rise of AI.

I cannot wait to hear what you think about it and if you could also leave an Amazon review, that would be fantastic! Thank you!

I’m looking forward to beginning this journey with you!

Here is the Amazon link: https://t.co/UFpiimPNVX

[Berci Meskó, MD, PhD @Berci]

I came across this video demonstration of how AI agents could ease the logistics of a dentistry clinic.

It's not a company or a verified tool, just a framework of ideas.

But it's still a good demo of tasks and challenges AI agents will be able to handle.

Please use this as an example to boost ideas about how AI agents will be able to help your business, medical practice, office or your personal day-to-day job.

I will literally spend all day today working on mine. Let's compare notes.

[Berci Meskó, MD, PhD @Berci]

Nature just covered a new gene therapy.

There are people with epilepsy resistant to drug treatment. After receiving a gene therapy, they saw the number of seizures they had per month fall by more than 90%!

"In each participant, the gene therapy was precisely targeted to a small patch of brain tissue that was the source of their seizures. The viruses carried a gene that makes neurons sensitive to a specific drug, which works like a dimmer switch for the therapy.

By combining gene therapy with a drug — an approach known as chemogenetics — researchers can adjust a treatment’s potency, which is not possible with other types of gene therapy."

Fortunately, the trial participants did not experience serious side effects and hopefully enough evidence will mount backing the treatment that it will soon become more widely used.

Big news for patients, the gene therapy research and business communities.

Source: https://t.co/4FeY28Vd0h

[Berci Meskó, MD, PhD @Berci]

In a year when big studies and papers come out that aim at achieving medical superintelligence (their wording, not mine), it was important for medical associations to help set the tone of such discussions.

Now, the American Medical Association (AMA) is drawing a clear line: AI can augment physicians and assist with clinical tasks, but it cannot be granted physician licensure, professional titles or certification to practice medicine.

"Adopted Monday at the AMA’s Interim Meeting, the policy calls for AI-enabled technologies to be integrated into physician-led teams and used at the direction of the treating physician.

AI tools used for clinical functions such as diagnosis, prescribing and care management should have transparent, auditable evidence demonstrating their safety and efficacy and be subject to appropriate regulation, documentation and liability requirements."

But it cannot be called a physician. Let's get used to this recommendation, because that is going to be the narrative of medical associations worldwide for many years to come.

Their announcement: https://t.co/LZoHq2UAs4

[Berci Meskó, MD, PhD @Berci]

BREAKING NEWS!

When ChatGPT Health and Claude for Healthcare launched earlier this year, I said let's see when Gemini for healthcare would launch, because it must happen. Here it is!

"The Gemini agent is a single, always-on agent for work where employees delegate an objective, and the agent plans the steps, retains organizational context, and routes across the best models to deliver finished outcomes inside the tools teams already use.

The Gemini agent is built with enterprise-grade identity administration, fine-grained access control, and centralized policy management directly into its runtime. Every agent operates with a distinct identity, inherits each user’s existing role-based permissions, and enforces strict need-to-know boundaries across every user, sub-agent, and workflow."

For example, it provides a patient’s history across care settings and prepares charts before the visit to reduce the number of denied claims.

It is HIPAA-compliant and is available starting today in preview.

Now that the big three AI companies have released their healthcare models, which one will win the race of trust and efficiency?

Source: https://t.co/To86rnOr3y

[Berci Meskó, MD, PhD @Berci]

@docwarsi Have you made any dietary changes based on the CGM results? I'm curious.

[Berci Meskó, MD, PhD @Berci]

Twice a year, I spend two weeks wearing a continuous glucose monitor (CGM). And I've just started another round! Why?

I'm curious about how my body responds to different dietary choices, types of exercise, and daily routines. I also have a strong family history of insulin resistance, so understanding my metabolic health is particularly important to me.

But here's an important distinction: I don't use a CGM to diagnose myself or chase perfect glucose curves.

I review the results with my primary care physician, who helps me interpret the data in the context of my overall health and regular laboratory tests.

We also need to acknowledge that while CGMs are invaluable for many people living with diabetes, the clinical benefits of routine glucose monitoring in people without diabetes are still not well established. Normal glucose fluctuations are not necessarily signs of a problem.
So for me, this is a personal experiment, not a medical recommendation.

As The Medical Futurist, I love experiencing health technologies firsthand. But I'm equally interested in understanding their limitations and distinguishing meaningful insights from simply having more data.

Do you use a CGM once in a while?

[Berci Meskó, MD, PhD @Berci]

@ExperimentWorld Nothing has been reported.

[Berci Meskó, MD, PhD @Berci]

Do you remember when in 2013, a man and a woman ate a world-historic burger, made from cattle cells grown in a laboratory that cost €250,000? 

The Guardian analyzes what has happened to lab-grown meat that was supposed to take over the world.

1. Billions were invested, but commercialization stalled. Around 140 companies emerged, attracting approximately $3 billion in investment. Yet funding declined dramatically after 2021, and cultivated meat remains almost entirely absent from supermarkets.

2. Scaling is the biggest technological challenge. Growing animal cells is scientifically possible, but manufacturing large quantities at competitive prices requires expensive bioreactors and complicated production processes. Producing something resembling a steak is particularly difficult.

3. Even the available products contain surprisingly little cultivated meat. The article describes a product sold in Singapore containing just 3% cultivated chicken cells, costing $5.62 for 110 grams. 

4. According to a survey cited in the article, only 18% of Americans find cultivated meat extremely or very appealing, while almost 60% say they are somewhat or very unlikely to buy it. 

Two final thoughts:

Scientific feasibility does not mean commercial viability. Just look at 3D-printed casts or organs.

Technological progress does not guarantee social acceptance. This is something we could all work on.

The article: https://t.co/BelTw5QBWN

[Berci Meskó, MD, PhD @Berci]

Medical Futures Studies is emerging as a new scientific field, applying established futures methods to explore how healthcare could evolve.

We launched the first dedicated theme issue in the Journal of Medical Internet Research, bringing together 14 studies demonstrating how these methods can be applied in medicine.

Here are the 14 papers from our JMIR theme issue, the futures methodologies they used and the questions they explored. https://t.co/mJ9vgpVuxp

[Berci Meskó, MD, PhD @Berci]

Why should you all use futures methods? I'll give you an example.

In this paper, we analyzed how large language models should be regulated in the future.

Analyzing how LLMs could be regulated now is an important piece of work. But pinpointing potential issues and challenges for the future could be a gold mine for regulators.

We discussed what will happen when LLMs can handle not only text but also video, audio, and images. They become multimodal before policy-makers can even blink. So providing regulations then will already be late.

Here we summarize what we can expect regulators to do about bringing LLMs to the practice of medicine.

1) Create a new regulatory category for LLMs as those are distinctively different from AI-based medical technologies that have gone through regulation already.

2) Provide regulatory guidance for companies and healthcare organizations about how they can deploy LLMs into their existing products and services.

3) Create a regulatory framework that not only covers text-based interactions but also possible future iterations such as analyzing sound or video.

4) Provide a framework for making a distinction between LLMs specifically trained on medical data and LLMs trained for non-medical purposes.

5) Similar to the FDA’s Digital Health Pre-Cert Program, regulate companies developing LLMs instead of regulating every single LLM iteration.

It's open access in npj Digital Medicine: https://t.co/7RRdiBnHeq

[Berci Meskó, MD, PhD @Berci]

Five years ago, I picked five healthcare technological trends I believed would shape the near future of medicine.

Now it's time to put my own expectations to the test.

In my new video, I revisit all five and compare what I expected with what actually happened.

As The Medical Futurist, I believe my work should be constantly challenged, tested, and evaluated. And I genuinely welcome that scrutiny.

Making predictions is easy. Coming back five years later, publicly examining your track record, and learning from it is far more interesting.

So, how did I do? https://t.co/TKIstmslfc

[Berci Meskó, MD, PhD @Berci]

Using AI in radiology was big news a decade ago. Then using for ultrasound imaging was big 5 years ago. Now AI-interpreted echocardiograms are comparable to human reports and can cut cardiologists’ time by about 50%!

"Cardiologists spent an average of 4.6 minutes per echocardiogram reviewing and finalizing AI-generated preliminary interpretations, compared with 8.5 minutes to generate interpretation reports without AI assistance, a time savings of about 46%.

These results demonstrate the potential for AI to improve the efficiency of everyday cardiology practice."

What's next? What if the next breakthrough isn't AI helping doctors interpret medical images, but proving that doctors don't need to review every single one?

Source: https://t.co/TVVHK54PuA

[Berci Meskó, MD, PhD @Berci]

A month ago, an OpenAI agent hacked into an Australian national healthcare database!

Now the Australian government has made some changes:

1) Australia will require AI companies to report breaches ‌and consider changes to criminal law to address "serious misconduct".

2) The mandatory AI safety and ​security protections will form part of the government's proposed AI legislation, which it plans to introduce in ​Parliament next year.

While at least they address the issue, isn't it a bit late? Using futures methods could help governments pinpoint such potential challenges and risks any maybe act on them in time.

What do you expect from your country's government regarding the use of AI in healthcare?

Source: https://t.co/pSUxp0wZ7p

[Berci Meskó, MD, PhD @Berci]

@cureourhurtmed https://t.co/yCpPmUavzN

[Berci Meskó, MD, PhD @Berci]

A technology adoption curve that shows 50 of the most promising digital health and AI technologies.

It shows what already has evidence, which ones are rising, and which trends are lagging behind.

I hope you find it useful.

If you need the full analysis, please comment 50, and I'll share the link with you.

[Berci Meskó, MD, PhD @Berci]

@maximilian_opp https://t.co/yCpPmU9XKf

[Berci Meskó, MD, PhD @Berci]

@worksleeve It's surprisingly good in the US: https://t.co/MlCbGvNTYO

[Berci Meskó, MD, PhD @Berci]

@fysioinzeist https://t.co/yCpPmUavzN

[Berci Meskó, MD, PhD @Berci]

Two years ago, I shared what I considered a major milestone for digital health: The FDA had qualified the Apple Watch's atrial fibrillation (AFib) History feature for use in clinical trials (making it the first digital health technology to enter its Medical Device Development Tools program).

I was excited about this back then, but I started wondering whether it has become standard practice.

Not yet, despite some progress.

1) First, the FDA qualification only covers a specific application: using weekly estimates of AFib burden as a secondary endpoint in clinical trials evaluating cardiac ablation devices. So it's not so easy to use it more widely.

2) Second, clinical studies are indeed moving forward: for example, Cleveland Clinic launched a trial comparing Apple Watch AFib History with traditional ECG patch monitoring after surgical ablation.

3) Third, a major international research consortium, AF-B-STEP, launched in 2026 to develop standardized methods for measuring AFib burden across medical devices and consumer wearables.

And the Apple Watch still appears to be the only consumer wearable on the FDA's list of qualified Medical Device Development Tools.

Not bad steps, but I still believe the potential is enormous. In short:

Regulatory acceptance opens the door, then clinical validation and standardization determine whether a technology becomes routine.

It also makes me wonder which wearable technology will be next to receive a similar FDA qualification.

[Berci Meskó, MD, PhD @Berci]

Do you remember the DeepMind and NHS story about sharing patients' retina scans without consent to get an AI model that can diagnose/predict the onset of diabetic retinopathy?

Something similar is going on again, and people are protesting against it.

"Palantir’s controversial £330m health contract is to be extended before ministers draw up plans to replace it with a British alternative.

The system aims to connect scattered medical files, speed up hospital discharges and improve surgery scheduling among other potentially life-saving improvements. But a review has concluded that removing Palantir from NHS data systems by triggering a break clause in its contract would be too disruptive, the FT reported."

The urge to use AI to decrease the amount of administration is clear and valid. But if the public is against it, then it is either not being communicated transparently enough or there is something fishy going on.

Either way, this story doesn't help build trust in healthcare AI systems, which is bad news for all of us.

Source: https://t.co/l30V1EzLjB