Medical Metrics, Inc.’s Post

Thanks Anirban Mukhopadhyay for inviting me to discuss Fairness of AI in Medical Imaging at the "AI-ready Healthcare podcast" supported by the MICCAI Society! We cover a wide range of topics, from the importance of fairness of AI in healthcare and the work we are doing with the FAIMI workshop, to how it is doing science in Latin America and building an AI community there with Khipu. For those interested, the papers we discuss are: - https://lnkd.in/eQ6ThgrP - https://lnkd.in/eiW7Tk6R

Wound Care friends, here's the next part of my discussion with Dr. Paul Kim about Generative AI in healthcare. This one is titled... "The Importance of Analytics in Wound Care" In this interview, we explore how advanced analytics are transforming wound care practices and improving patient outcomes. You may watch the full interview here: https://lnkd.in/es_QWkEf Please share your thoughts on this topic below. Thank you! #ArtificialIntelligence #GenerativeAI #WoundCare

Just sent the weekly PYCAD newsletter. In this edition I cover the expected project lifecycle of a Medical AI project. You can check out last week's edition here: newsletter.pycad.co

No two patients are the same, and precision medicine is now allowing healthcare professionals to tailor patient treatment to the specific needs of each individual. By blending software, AI, and analytics, precision medicine is becoming more accessible and is now a common trend in the healthcare industry. Check out this article to learn more about precision medicine! #precisionmedicine #advacement

My blog is updated. The latest post demonstrates how search algorithms from AIMA's Chapter 4 can be applied to healthcare resource allocation, focusing on optimizing mobile clinic deployment in underserved areas. It covers methods ranging from hill-climbing to genetic algorithms and reinforcement learning, illustrating their potential impact on healthcare logistics. The article aims to bridge theoretical AI concepts from AIMA with real-world challenges, offering potential insights into improving service distribution. Check out the full article at the following link

Though benchmarks for medical AI are still imperfect, there's no question that AI will continue to march towards diagnostic excellence. These trends will place greater emphasis on physician-scientists – those who advance medical knowledge via closed loop clinic/lab interfaces, which can then feed back into large-scale AI systems that serve entire populations. This was all part of the OG vision for the learning health system. source: https://lnkd.in/eh2RM72s

A view of GenAI getting closer to true diagnostics. Not nearly there, but a few steps ahead with each new model release…

Great to see practical applications of Generative AI in healthcare and specific therapeutic experiences. Color Health seems to be using GPT-4o's vision capabilities, on top of just synthesising patient records (text data) By answering key questions like, “What screenings should the patient be doing?” the application identifies missing diagnostics and generates personalized screening plans.

The novel insights in the use of AI in the medical practice at #ESVS2024. next step; reduce the administrative tasks and embed these diagnostic tools in daily practice

From unlocking hidden biomarkers to streamlining administrative burdens, AI will improve patient care and redefine the role of physicians. After sifting through hundreds of technologies, I have 10 predictions for healthcare AI, coming from four distinct facets of the healthcare spectrum. I'll share my predictions with you in this video!🙂