Global Peter Drucker Forum’s Post

In this video, I discuss my 2021 research on using AutoML to predict patient outcomes from COVID-19, conducted during my residency at Montefiore Medical Center. Despite the fast-paced evolution of ML and the waning of COVID-19, the core of my presentation is the critical evaluation of ML models from a clinical/epidemiological perspective. Having the skills to critically evaluate ML models is essential as AI continues to advance. Hope it is helpful! 😊 Part 1: https://lnkd.in/e5SQCAxq Part 2: https://lnkd.in/emspVGR2 #ml #ai #covid19 #medicaleducation #clinicalinformatics

AI predicts diseases with 98% accuracy in real-time using tongue color An AI-powered model can diagnose diseases with 98% accuracy by analyzing the color of a patient's tongue. This technology replicates an ancient practice from traditional Chinese medicine, where tongue color, shape, and thickness indicate various health conditions. The AI was trained using 5,260 images and six machine learning algorithms to recognize different tongue colors associated with specific diseases, such as diabetes, stroke, anemia, and COVID-19. This system allows for real-time, on-the-spot disease diagnosis, potentially speeding up the process in healthcare settings. #AIHealthcare #MedicalInnovation #HealthTech #ArtificialIntelligence

Remember mad cow disease? A common practice – feeding cows the ground-up remains of other cows – led to a neurological disorder that could even spread to humans. The panic was palpable as we figured out how to untangle that mess. In the world of AI, something similar is happening, and researchers at Rice University have labeled it "model autophagy." As AI models are trained on the outputs of other models, they're ingesting and amplifying each other's biases, errors, and limitations. This self-referential cycle, if left unchecked, can lead to a condition they've called Model Autophagy Disorder (MAD) (who doesn't love an acronym). In summary, models are what they eat - is your AI model being fed 'fresh veggies,' or is it consuming an unhealthy helping of 'ground-up model leftovers'? #machinelearning #dataquality

AI Daily: AI CURES DISEASES Plus AI Blows Through Bottlenecks YOUTUBE EDITION. Discover the potential and challenges of AI in various domains, from biochemistry to decision-making, employment, culture, health, and art.

AI Daily: AI CURES DISEASES Plus AI Blows Through Bottlenecks YOUTUBE EDITION. Discover the potential and challenges of AI in various domains, from biochemistry to decision-making, employment, culture, health, and art. https://lnkd.in/gwjVUuNz

Successfully completed 'AI in Health Care'certification Course from Great learning Platform. From this course I learned lot of things such as how AI helpful in diagnosing diseases, predicting outcomes, and recommending treatments for different diseases. AI Definitely became a integral part of Health Sector in upcoming years. #greatlearning #artificialintelligence #pharmacystudent #certificationcourse #aiinhealthcare #pharmacists #skillsdevelopment

Unlock the secrets of cellular processes with #AI. Discover how #deeplearning models like #AlphaFold reveal crucial protein-DNA interactions, paving the way for advanced disease therapies. #drugdiscovery #healthcare

Unlock the secrets of cellular processes with #AI. Discover how #deeplearning models like #AlphaFold reveal crucial protein-DNA interactions, paving the way for advanced disease therapies. #drugdiscovery #healthcare

Doctors always want to treat #diseases at the early stages. #AI will have the ability to not only treat but predict and prevent through advanced #medical #diagnostics. With AI on the horizon, the future of medicine isn't just about treating diseases; it's about #predicting and #preventing them altogether. Here's to a healthier tomorrow powered by #innovation! #Humans and #AI working together will increase life. Dr. Mahboob Khan

AI-supported cough diagnosis? Absolutely! Google scientists have developed a machine-learning system trained on millions of human audio clips that could revolutionize healthcare. The tool, called Health Acoustic Representations (HeAR), evaluates noises like coughing and breathing to detect and monitor diseases like COVID-19 and tuberculosis. While sound has been explored as a biomarker for disease before, what sets HeAR apart is the massive data set it was trained on and its ability to perform multiple tasks. Although it's too early to tell if HeAR will become a commercial product, interested researchers can access the model for their own investigations. This breakthrough could change the way we diagnose and treat diseases in the future. #AI #healthcare #machinelearning #COVID19 #tuberculosis