How AI can Assist Medical Professionals

There has been a lot of speculation about how willing physicians will be to accept clinical guidance from AI. It’s an understandably touchy subject. Physicians are rightfully proud of the education, experience and expertise that informs their decisions. So what happens when AI tells them to reconsider? A recent study from colleagues at Stanford found that doctors would revise their medical decisions in light of new AI-generated information. Here are the details (https://lnkd.in/eDsp_zxb): ·      50 physicians were randomized to watch a short video of either a white male or black female patient describing their chest pain using an identical script ·      The physicians made triage, diagnosis, and treatment decisions using any non-AI resources ·      The physicians were then given access to GPT-4 (which they were told was an AI system that had not yet been validated) and allowed to change their decisions. They used it to bring in new evidence, compare treatments and challenge their own beliefs. The non-AI scores were not great: - 47% accuracy in the white male patients and 63% accuracy in the black female group. However, after using AI, - accuracy increased to 65% in the white male group and 80% in the black female group. Not only were the physicians open to changing their decisions using AI, but it made them more accurate without introducing biases. A post-study survey indicated that 90% of physicians expect AI tools to play a significant role in future clinical decision making. The results are encouraging for more accurate and equitable care, and I give credit to the physicians willing to adjust their decisions based on AI input. Buy-in from clinicians and other users is critical for genAI to achieve its full potential.   #HealthcareAI #AIAdoption #HealthTech #GenerativeAI

Did you see the recent news??? Microsoft recently unveiled its latest AI Diagnostic Orchestrator (MAI DxO), reporting an impressive 85.5% accuracy on 304 particularly complex cases from the New England Journal of Medicine, compared to just ~20% for physicians under controlled conditions . These results—quadrupling the diagnostic accuracy of human clinicians and more cost-effective than standard pathways — have gotten a lot of buzz. They may mark a significant milestone in clinical decision support and raise both enthusiasm but also caution. Some perspective as we continue to determine the role of AI in healthcare. 1. Validation Is Essential Promising results in controlled settings are just the beginning. We urge Microsoft and others to pursue transparent, peer reviewed clinical studies, including real-world trials comparing AI-assisted workflows against standard clinician performance—ideally published in clinical journals. 2. Recognize the value of Patient–Physician Relations Even the most advanced AI cannot replicate the human touch—listening, interpreting, and guiding patients through uncertainty. Physicians must retain control, using AI as a tool, not a crutch. 3. Acknowledge Potential Bias AI is only as strong as its training data. We must ensure representation across demographics and guard against replicating systemic biases. Transparency in model design and evaluation standards is non-negotiable. 4. Regulatory & Liability Frameworks As AI enters clinical care, we need clear pathways from FDA approval to liability guidelines. The AMA is actively engaging with regulators, insurers, and health systems to craft policies that ensure safety, data integrity, and professional accountability. 5. Prioritize Clinician Wellness Tools that reduce diagnostic uncertainty and documentation burden can strengthen clinician well-being. But meaningful adoption requires integration with workflow, training, and ongoing support. We need to look at this from a holistic perspective. We need to promote an environment where physicians, patients, and AI systems collaborate, Let’s convene cross sector partnerships across industry, academia, and government to champion AI that empowers clinicians, enhances patient care, and protects public health. Let’s embrace innovation—not as a replacement for human care, but as its greatest ally. #healthcare #ai #innovation #physicians https://lnkd.in/ew-j7yNS

Everyone asks if AI will replace doctors. It's the wrong question. The right one is how can AI help overwhelmed clinicians deliver better care? What we're really building: • Tools that spot patterns humans might miss • Systems that reduce administrative burdens • Technology that makes medical knowledge more accessible The National Academy of Medicine report urges wider AI adoption across medicine. Building effective healthcare AI means confronting: Data biases (like algorithms that only work on light skin) The hallucination problem (AI confidently citing non-existent research) Integration with legacy systems (healthcare IT is notoriously complex) We discovered that discovered that the most powerful applications aren't about replacing clinical judgment - they're about enhancing it. The doctor who spends 20 minutes analyzing a scan? AI helps them do it in 2. The nurse tracking medications across 12 patients? AI reduces errors by 63%. But technology without human insight is dangerous. When we tested Hana with clinicians, they spotted limitations our engineering team missed. This isn't about AI vs. humans. It's about AI + humans creating something better than either could alone. The future of healthcare isn't machine replacement. It's augmented intelligence.