Tag: diagnosis
-
Claude, what’s going on in this picture?
A post where I give Claude two images and simply ask it to describe what it sees. The responses come awfully close to what we might call ‘diagnosis’.
-
Podcast – AI and the Evolution of Medical Thought
In this episode of the AI Grand Rounds podcast, Dr. Adam Rodman shares his unique journey from a historian to a physician deeply interested in the intersection of medicine and artificial intelligence.
-
Artificial Intelligence and the Future of Primary Care
The rapid advancement of AI in primary care is outpacing professional expectations. A 2019 study showed GP skepticism about AI’s potential in diagnosis and patient interaction. However, recent developments like Google DeepMind’s AMIE demonstrate AI’s superior performance in these areas, highlighting the need for the medical field to adapt quickly to technological changes.
-
Link: Use of GPT-4 to Diagnose Complex Clinical Cases
https://ai.nejm.org/doi/full/10.1056/AIp2300031 “We assessed the performance of the newly released AI GPT-4 in diagnosing complex medical case challenges and compared the success rate to that of medical-journal readers. GPT-4 correctly diagnosed 57% of cases, outperforming 99.98% of simulated human readers generated from online answers. We highlight the potential for AI to be a powerful supportive tool…
-
Symposium – Beyond thinking fast and slow: Theories informing teaching and assessment of clinical decision-making and error
in Conferenceaffordance, ai, AMEE, AMEE23, artificial intelligence, bais, chunk, clinical reasoning, cognitive debiasing, collective intelligence, diagnosis, diagnostic error, distributed cognition, dual-process theory, ecological psychology, embodied cognition, error, extended mind, illness schema, illness script, information, philosophy of mind, reasoning, situated cognition, system 1, system 2, technology affordance, transtheoretical modelThis is going to be a long post, as it includes an expansion of the notes I took during this symposium. It’s hard to draw a bright line between the presentation content and my extended notes, so I think it’s fair to say that what’s presented below isn’t an accurate description of what was presented.…
-
On the poor performance of AI models during the pandemic
Heaven, W.D. (2021). Hundreds of AI tools have been built to catch covid. None of them helped. MIT Technology Review. In the end, many hundreds of predictive tools were developed. None of them made a real difference, and some were potentially harmful. That’s the damning conclusion of multiple studies published in the last few months.…
-
The first AI approved to diagnose disease is tackling blindness in rural areas
There are any number of reasons why people don’t get medical care or don’t follow up on a referral to a specialist. They might not think they have a serious problem. They might lack time off work, reliable transportation, or health insurance. And those are problems AI alone can’t solve. Source: Mullin, E. (2018). The…
-
Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices
Based on these results, FDA authorized the system for use by health care providers to detect more than mild DR and diabetic macular edema, making it, the first FDA authorized autonomous AI diagnostic system in any field of medicine, with the potential to help prevent vision loss in thousands of people with diabetes annually. Source:…
-
DeepMind’s AI can detect over 50 eye diseases as accurately as a doctor.
This is the point at which the risk from medical AI becomes much greater. Our inability to explain exactly how AI systems reach certain decisions is well-documented. And, as we’ve seen with self-driving car crashes, when humans take our hands off the wheel, there’s always a chance that a computer will make a fatal error…
-
Defensive Diagnostics: the legal implications of AI in radiology
Doctors are human. And humans make mistakes. And while scientific advancements have dramatically improved our ability to detect and treat illness, they have also engendered a perception of precision, exactness and infallibility. When patient expectations collide with human error, malpractice lawsuits are born. And it’s a very expensive problem. Source: Defensive Diagnostics: the legal implications…
-
IBM’s Watson gave unsafe recommendations for treating cancer
In 2012, doctors at Memorial Sloan Kettering Cancer Center partnered with IBM to train Watson to diagnose and treat patients. But according to IBM documents dated from last summer, the supercomputer has frequently given bad advice, like when it suggested a cancer patient with severe bleeding be given a drug that could cause the bleeding…
-
Why AI Doesn’t Threaten Doctors
But while the cold perfection of A.I. makes for a more perfect medical diagnosis, it can’t replace a human. After all, we love and embrace physicians who approach their work with empathy for patients and a warm understanding of what their fellow human beings are going through. Source: Why AI Doesn’t Threaten Doctors I don’t…
-
A.I. Versus M.D. What happens when diagnosis is automated?
The word “diagnosis,” he reminded me, comes from the Greek for “knowing apart.” Machine-learning algorithms will only become better at such knowing apart—at partitioning, at distinguishing moles from melanomas. But knowing, in all its dimensions, transcends those task-focussed algorithms. In the realm of medicine, perhaps the ultimate rewards come from knowing together. Source: A.I. Versus…