Meet the AI news guru

From: POLITICO Future Pulse - Thursday Feb 08,2024 07:02 pm
The ideas and innovators shaping health care
Feb 08, 2024 View in browser
 
Future Pulse

By Daniel Payne, Erin Schumaker and Ruth Reader

TECH MAZE

Dr. Zak Kohane

Dr. Zak Kohane | Peter Gumaskas

Dr. Zak Kohane is the first editor-in-chief of the New England Journal of Medicine’s new artificial intelligence publication.

He also chairs the Department of Biomedical Informatics at Harvard Medical School and has rare dual expertise as a medical doctor and a doctor of computer science.

He talked with Daniel about how to cut through the noise and determine which of the AI health hype is worth watching.

This interview has been edited for length and clarity.

Is AI really going to revolutionize care?

I think there’s an enormous amount of hype. And I think, by any metric, the number of companies that will make a meaningful contribution in five years is going to be a minority.

And yet, I think that minority — an important, decisive minority — will be enormously impactful.

Where will we see that impact?

Primary and preventive care is now dissolving. That’s what we’re facing.

It’s in that context that the question is not: “Is this going to change things?” It's really: “Well, things are changing anyway, but there are huge disparities.”

How can we best leverage the workforce we have — not the one we want?

We have very well-trained physician assistants and nurse practitioners. How can we use AI in concert with these individuals to provide primary and preventive care?

What are you expecting in the coming months and years?

The pace of change is accelerating, so a lot of the problems that we know about — whether it’s bias, hallucination, not being up to date, not having common sense — those problems will not look the same next year.

It’s going to be, I think, unlike anything we’ve seen in the last 30, 40 years of medicine.

Is the government ready for that?

No.

Frankly, most of us would not even know what to tell the government to do in this situation.

So I think it’s appropriate that the government is saying that, as part of Biden’s executive order, we have to start putting together people who know stuff about this and start thinking about it.

 

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New Harbor, Maine | Shawn Zeller/POLITICO

This is where we explore the ideas and innovators shaping health care.

The power of “uplifts.” Simple activities can improve mood after a traumatic loss, according to new research. So-called uplifts, like completing a task, getting enough sleep, dining out, spending time with family or contacting a friend, served as positive counterbalances for people coping with a loved one’s death.

Bonus: The findings held true regardless of socioeconomic status or age.

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CHECKUP

A dermatologist checks moles on a patient on May 22, 2019 in Quimper, western France. (Photo by Fred TANNEAU / AFP) (Photo by FRED TANNEAU/AFP via Getty Images)

The AI of today can improve dermatology, but it won't eliminate bias, a new study found. | AFP via Getty Images

AI could make doctors better at their jobs — but don’t expect that to eliminate the bias that’s long plagued the health system.

How’s that? A new study in Nature Medicine by researchers at Northwestern, MIT, Stanford and others found that an AI system could help doctors come to the right diagnosis more often.

But the gains weren’t always distributed evenly, with more improvement tied to patients with lighter skin.

The study looked at how an AI system affected the diagnoses of dermatologists and primary care physicians.

The AI system was good at diagnosing across skin tones, according to the paper’s authors, and the doctors — 459 primary care physicians and 389 dermatologists — could diagnose a disease more accurately when they used it.

But the primary care physicians improved more diagnosing patients with light skin than with darker skin tones.

Takeaway: AI could be a powerful tool to improve care and potentially offer providers a check on their blindspots.

But that doesn’t mean AI will reduce bias. In fact, the study suggests, AI could cause greater disparities in care.

 

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THE LAB

Drug capsules are pictured on the production line at the plant of French multinational pharmaceutical company "Pierre Fabre", in Gien on March 21, 2018. The Gien site is the group's most important production site. It manufactures and packages dry (hard capsules, tablets, sachets), paste and liquid forms under pharmaceutical, dermo-cosmetic, and medical device status. (Photo by GERARD JULIEN / AFP) (Photo by GERARD JULIEN/AFP via Getty Images)

Drugmakers are rushing to use AI to develop new medicines. | AFP via Getty Images

Scientists are using AI to identify promising drugs and, crucially, understand better how and why those drugs work, according to a study by University of Virginia researchers.

The research, published in Proceedings of the National Academy of Sciences, describes developing a computer model to identify heart drugs that could reduce scarring after a heart attack — and possibly produce better patient outcomes.

How so? The research team trained its machine-learning model on decades of human knowledge about the effect drugs have on fibroblasts, a type of connective tissue cell that helps repair the heart after an injury but can leave scarring.

Past attempts to identify drugs to reduce scarring have generally been unsuccessful, partly because of a knowledge gap — it’s often unclear how the drugs worked.

“On its own, machine learning helps us to identify cell signatures produced by drugs," Jeffrey Saucerman, study co-author and biomedical engineering professor at UVA, said in a statement.

“Bridging machine learning with human learning helped us not only predict drugs against fibrosis [scarring] but also explain how they work. This knowledge is needed to design clinical trials and identify potential side effects.”

In the paper, the team studied the effects of 13 promising drugs on human fibroblasts. They used that data to train the model to predict how drugs affect cell behavior. The model predicted how one Food and Drug Administration-approved drug suppresses fibroblast fibers that stiffen the heart.

Reality check: While Saucerman is optimistic about the potential for understanding how new drugs work, more research is needed to see whether the drugs are effective in animal models and human patients.

 

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