Jens Hollmann’s Post

Our dear Prof. Nigam Shah is AMAZING as always! ✨ Wonderful session by Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). The future of medicine and healthcare is here, indeed. #KPJU #KPJHealthcareUniversity #StanfordAIMI #AIMedicine #DigitalHealth #FifthGear

A dynamic presentation by AIMI Co-director Nigam Shah and an engaging panel discussion featuring AIMI affiliated faculty Fatima Rodriguez, MD, MPH, and Stanford colleagues Alex Weihan Chu and Michael Pfeffer demonstrated the vital role of AI in health care, and emphasized the importance of using it safely, ethically, and cost-effectively. Drs. Shah and Rodriguez's fascinating insights -- shared as part of the "Artificial Intelligence: The Future of Medicine & Health Care Is Here" live event -- showed how Stanford is at the forefront of medical innovation by using AI responsibly for the benefit of the Tri-Valley community and beyond. From the 'Green Button Project' to enhancing patient prognostic models, Dr. Shah discussed how AI is playing a pivotal role in advancing clinical decision-making and patient care at Stanford. He also emphasized the need to ensure benefits of Large Language Models (LLMs) in medical implementations. In the panel discussion, Dr. Rodriguez shared her insights on an initiative that is underway to use an AI model to analyze existing imaging data to find patients at risk of heart disease, and then deliver subsequent—and often lifesaving—preventive care. Want to learn more about the potential of AI to advance health care? Watch Dr. Shah's full presentation: https://bit.ly/3XF6QOu Watch the full panel discussion with Dr. Rodriguez: https://bit.ly/4de3GqA The event included opening and closing remarks by Stanford Health Care Tri-Valley President and CEO Rick Shumway. #Datasets #LargeLanguageModels #AIinHealthcare #InnovationInMedicine #PatientCare

The Impact of Artificial Intelligence on Internal Medicine Physicians: A Survey of Procedural ...: Background: Artificial intelligence (AI) is increasingly being integrated into various aspects of healthcare, including internal medicine. http://dlvr.it/TD5mhM

Emergency medicine serves as the frontline of healthcare and the integration of AI, and clinical decision support at this critical care point has the potential to revolutionize the way care is delivered. #HealthcareAI #Clinical #CriticalCare

A way to get some insight as to what is practical AI and Philips approach to AI innovation. #Philips #AI

From earlier diagnoses, improving patient outcomes, to streamlining operations, the potential for AI in Healthcare and medicine is immense. As we navigate this rapidly evolving field, it’s crucial to stay informed about the latest advancements and their implications. Tune in below for more information!

Navigating the doctor-patient-AI relationship - a mixed-methods study of physician attitudes toward artificial intelligence in primary care Artificial intelligence (AI) is a rapidly advancing field that is beginning to enter the practice of medicine. Primary care is a cornerstone of medicine and deals with challenges such as physician shortage and burnout which impact patient care.

✌️ The 2nd edition of NEJM AI is here! This edition includes an overview of how the journal is committed to the publication of "clinical-grade evidence needed to improve patient care with AI." Viz.ai is a proud sponsor of this journal and we strongly support the exploration of the cutting-edge applications of artificial intelligence and machine learning in clinical medicine. Check out the latest edition here: https://lnkd.in/evqUu6yC #AIinMedicine #PatientsFirst #AIinHealthcare

🔷 The Language of Medicine Is Changing 🔷 Optimizing clinical dialogues with LLMs: enhancing care, not complexity. 🔵 LLMs have the potential to transform health care, but effective prompting is key to unlocking their utility. 🔵 Context-rich inputs and iterative refinement enhance the accuracy and relevance of LLM responses. 🔵 Seamless integration of LLMs into clinical workflows is crucial to avoid overburdening clinicians. https://lnkd.in/eDE-nZpQ #AI #LLMs #medicine #digitalhealth

When the traditional clinical trial format meets AI, magic happens. This was obvious listening to the expert panel discussing how AI is enhancing clinical trials today and the potential for future. From identifying potential subjects through rapid and more complex data mining, using digital twins, to real time patient tracking that does not burden the clinician with mundane tasks, the opportunities are endless. What also stood out in the conversation were the universal "Janitorial" data challenges that impact all healthcare and life science projects trying to use data in AI models, across the Payer, Provider Pharma/Biotech continuum: Bad data/ heterogeneity of data/ old data Biases in data Lack of understanding and appreciation of "data flows" in the system, which truly derail projects Inadequate investments in the non-glamorous but crucial "data foundation" More interesting, these issues are not new ones. They have existed before this age of AI. Remember the days of receiving multi year worth of clinical trial data on a 18-tabbed excel sheet? the "blank cells" which could mean either missing data or "N/A"? and if you also had omic data, well.... the sample IDs differing by one alphabet could tailspin you down a few hours!! Yes, those annoying, "low value" tasks, which have magnified their impact in the age of big-data. As we look forward to using AI to it's fullest, we also need to really appreciate the importance of expert/SME curated, solid data foundations. This will likely require some new and unusual partnerships too! The future is bright, and road is bumpy. And if we can send man to moon, make aids history, we can solve the data challenges too! #precisionmedicine #AI