| | | Virtually going toe-to-toe with medical doctors taking questions from real-world patients, a generative AI chatbot gave superior medical advice almost 80% of the time. What’s more, response evaluators consistently scored the technology—yes, a ChatGPT model—higher than the doctors for empathy and, with it, bedside manners. The online competition was conducted by John W. Ayers, PhD, and colleagues at UC-San Diego. It’s described in JAMA Internal Medicine. Here’s more. - Evaluators didn’t know which responses came from which contender, ChatGPT vs. verified doctor. The research team used textual material from around 200 randomly grabbed 1-to-1 exchanges at Reddit’s r/AskDocs forum.
- The blinded evaluator panel consisted of four physicians and one nurse practitioner. Together they brought experience in pediatrics, geriatrics, internal medicine, oncology, infectious disease and preventive medicine.
- For each blinded Q&A pair, the judges picked one response as the “better” of the two. They rated information quality on a 5-point scale—very good, good, acceptable, poor or very poor—and did the same for perceived sensitivity to patients’ feelings (very empathetic, empathetic, moderately empathetic, slightly empathetic or not empathetic).
- For overall informational quality—accuracy, thoroughness, usability—chatbot responses topped those from physicians in 78.6% of 585 evaluations. Indeed, the chatbot rang up scores of “good” or “very good” 3.6 times more than did the physicians.
- The chatbot trounced the doctors at making patients feel heard. The panel deemed the chatbot empathetic or very empathetic at a rate some 9.8 times higher than the physicians managed.
The authors conclude: Further exploration of this technology is warranted in clinical settings, such as using [a ChatGPT] chatbot to draft responses that physicians could then edit. Randomized trials could assess further if using AI assistants might improve responses, lower clinician burnout and improve patient outcomes.”
Read the full study here and coverage by UC-San Diego’s news team here. |
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| | | Buzzworthy developments of the past few days. - The doctor doesn’t always know best. And neither will the AI. So warns a writer at MIT Technology Review after reading a journal paper on the risks of “algorithmic paternalism.” The key danger? “Doctors may be inclined to trust AI at the expense of a patient’s own lived experiences—as well as their own clinical judgment.” MIT article here, journal paper here.
- Here’s one answer to mental healthcare staffing shortages. Eleos Health of Boston is introducing a web-based, AI-aided application aimed at behavioral healthcare workers who travel to treat clients. The company says the software helps these often-harried workers spend less time on unbillable administrative tasks and more time on clinical care.
- What next with ChatGPT? Electronic dreams? An academic physician is wondering out loud whether a future iteration of generative AI will develop subconscious cognition on top of a will of its own. While acknowledging the outlandishness of the notion, the medical scholar observes: “[I]t is nonetheless remarkable that discussions in these directions are currently unfolding, even among seasoned AI researchers.” Peer-reviewed paper here, coverage by Radiology Business here.
- Investors warm up to pharmaceutical facilitators. Toronto-based Odaia has raised $25 million in Series B funds to refine its SaaS product for pharma companies looking to commercialize and market new drugs. The company says its lead product, Maptual, uses AI to “streamline and automate the prospecting, qualifying and engagement of healthcare providers, a process that has largely been manual, labor intensive and time consuming.”
- High hopes for low back AI. Smart Soft Healthcare (SSHC) of Varna, Bulgaria, is working with AI platform company Osimis of Liège, Belgium, to distribute SSHC’s AI-based software for reading lumbar MRI scans. SSHC says the toolkit, called CoLumbo AI Spine Assistant, helps detect and diagnose such conditions as herniations, stenosis and other MSK pathologies of the low back. Announcement here.
- Collaboration in industry’s corner. Healthcare cloud supplier Greenlight Guru (Indianapolis) is partnering with engineering company HTec Group (San Francisco) on digital architecture for medical device manufacturers and AI startups looking for zippier navigation of regulatory and compliance processes. Announcement here.
- Until mere moments ago in technological history, not many people believed AI could actually get smarter than people. Indeed, “most people thought it was way off. And I thought it was way off. I thought it was 30 to 50 years or even longer away. Obviously, I no longer think that.” The quote is notable because of who said it: 75-year-old Geoffrey Hinton, the “Godfather of AI,” who just left Google so he can—as he clarified on Twitter (@geoffreyhinton)—“talk about the dangers of AI without considering how this impacts Google.” New York Times news analysis here, much follow-up coverage here.
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| | | - Digital Magazine: This is Enterprise Imaging - In this digital magazine we talk about how moving from multiple PACS to a single enterprise imaging system is busting siloes and deepening integration; challenges in radiology imaging and how radiologists are getting more done—better and faster—by using enterprise imaging; skyrocketing image volume and an increased need for collaboration across multiple and geographically diverse sites has made image management far more complex and why cloud is a solution to this; our latest addition to Sectra Enterprise Imaging portfolio—ophthalmology and why it is a game-changer for ophthalmologists.
Beyond the impression: How AI-driven clinical intelligence transforms the radiology experience - In this session, Nuance CMIO Sheela Agarwal, MD, and Senior Product Manager Luanne D’Antoni explore innovations in radiology report creation and the role of automated impression generation. AI quality assurance models saving lives and millions in avoided med-mal - Unrecognized imaging findings are an unfortunate, but undeniable, part of radiology. New advancements in artificial intelligence (AI) and machine learning offer a critical safety net that is improving care and saving lives — as well as avoiding millions of dollars in potential medical malpractice costs.
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