"How well does the AI perform clinically? And my answer is, I'm stunned to say: Better than many doctors I've observed."--Isaac The large language model GPT-4 (LLM, aka generative AI chatbot or foundation model) was just released 2 weeks ago (14 March) but there's already been much written about its advance beyond ChatGPT, released 30 November 2022, "the most successful new product in the history of the western world" with over 100 million users in just 2 months. A new book by Peter Lee, Carey Goldberg, Isaac Kohane will be released as an e-book April 15th and as a paperback May 3rd and I've had the chance to read it. With my keen interest for how AI can transform medicine (as written about in Deep Medicine and multiple recent review papers here, here, here), I couldn't put it down.

AI in medicine is basically a single mode story to date. Help reading an X-ray or MRI, finding polyps during a colonoscopy, provide patient coaching for a specific condition like diabetes, or a preliminary diagnosis of a skin lesion or heart rhythm from a smartwatch recording. It has largely been image-centric to date, with minimal integration with, or use of inputs from, text and voice. But over time that narrowness and constraint may well be alleviated. My colleagues and I recently wrote a review of the potential for multimodal AI, when data from many sources can be ingested and processed as seen below.

Eric Topol is a leading health expert whose writing and explainers about Covid-19 have helped people better understand the complexities of the global pandemic. As a doctor, author, and one of the most cited researchers in medicine, Eric has dedicated his time to thinking about the human genome and how digital tools like artificial intelligence can help us individualize and improve medicine. In this episode, he shares his thoughts why he believes healthcare and the doctor-patient relationship feel broken, and how AI can revolutionize–and save–the future of medicine.

He thinks AI...is set to save time, lives and money."―The Economist "Topol passionately and persuasively sets out the transformational potential of deep medicine."―Lancet "[Topol's] argument for using technology to bring care back to health care is timeless."―Nature "An optimistic vision of medicine's rapidly approaching future that should be required reading for the public and medical people alike."―Booklist "Enlightening... Anyone with an avid curiosity about the future of medicine will find this worthwhile."―Publishers Weekly "A gimlet-eyed look at the role of computers in medicine...A cogent argument for a more humane -- and human -- medicine, assisted by technology but not driven by it."―Kirkus "Eric Topol has a unique knack for bringing us to the frontiers of medicine in his books, and this one is no exception.

Recent surveys, studies, forecasts and other quantitative assessments of AI highlight the role AI plays in fighting the Coronavirus, the business impact of AI, and what the American public feels about it. UC San Diego Health developed and applied an artificial intelligence algorithm to more than 2,000 lung X-ray images, helping radiologists more quickly identify signs of early pneumonia in Covid-19 patients [Becker's Hospital Review] Mayo Clinic teamed up with the state's health department to create an artificial intelligence-powered tool that can identify zones of greater Covid-19 transmission in southern Minnesota [Becker's Hospital Review] The FluSense model, developed by researchers at University of Massachusetts Amherst, was tested in campus clinic waiting rooms. The AI platform was able to analyze coughing sounds and crowd size collected by the handheld device in real-time, then use that data to accurately predict daily illness rates in each clinic [Becker's Hospital Review] The Rambam Hospital in Haifa, Israel, has begun a clinical trial of Cordio Medical's app-based AI system that analyzes speech to diagnose and remotely monitor Covid-19 patients [VentureBeat] Kentucky-based Baptist Health is using an AI platform from remote-patient-monitoring startup Current Health Ltd. to track about 20 Covid-19 patients [WSJ] AI startup SparkBeyond will assist Argentina in looking at how the country can allow citizens to return to work and minimize economic impact. The platform will use data from the Argentinian ministry of health, which aggregates travel, demographic and employment data for each citizen, then integrates hundreds of external data sources to create a wider picture of the situation. It is an area where any country, even countries as big as China and the United States, will find it challenging to achieve the necessary scale of data--from tens to hundreds of millions of humans--to train machine-learning applications that generate robust insights into health and disease.

AI is transforming the practice of medicine. It's helping doctors diagnose patients more accurately, make predictions about patients' future health, and recommend better treatments. To help make this transformation possible worldwide, you need to gain practical experience applying machine learning to concrete problems in medicine. We've gathered experts in the AI and medicine field to share their career advice and what they're working on. We'll also be celebrating the launch of our new AI For Medicine Specialization!

The FDA has cleared what it describes as the first software that uses AI to guide family doctors, registered nurses and other clinicians in taking cardiac ultrasounds. Developed by Brisbane, California-based Caption Health, the software communicates instructions via prompts on a screen-based interface. The prompts allow non-experts to capture images and videos of diagnostic quality. "This is especially important because it demonstrates the potential for artificial intelligence and machine learning technologies to increase access to safe and effective cardiac diagnostics that can be life-saving for patients," Robert Ochs, a deputy director in the FDA's Center for Devices and Radiological Health, said in a statement. The software is called Caption Guidance and was cleared for use with a diagnostic ultrasound system developed by Teratech Corp., though the software has the potential to be used with other systems, according to the FDA. In granting clearance to the software, the agency said it looked at two independent studies.

Recently, Dr. Eric Topol captured vivid images of his heart, abdomen and left foot, among other things, using only a handheld ultrasound tool and a smartphone. "A total-body medical selfie," said Topol Wednesday at the CHIME19 Fall CIO Forum in Phoenix, where the photos were projected onto screens during his closing keynote address. "This all took a matter of minutes." But when Topol experienced abdominal pain, his doctor ordered a standard CT scan, which ultimately captured the same details. SUBSCRIBE: Become an Insider for access to exclusive HealthTech videos, white papers and articles.

Combining the power of humans and machines--intelligence both human and artificial--would take medicine to an unprecedented level.

He thinks AI...is set to save time, lives and money."―The Economist "Topol passionately and persuasively sets out the transformational potential of deep medicine."―Lancet