Tanat Tonguthaisri, CISSP®’s Post

Would you trust a computer to hold your health in its silicon hands? "Michelangelo warned, ‘The greatest danger… is not that our aim is too high and we miss it, but that it is too low and we reach it.’ Chilling, right? Yet, that's the future digital twins could bring: personalized medicine, predicting our outcomes before we even blink. Professors Coveney & Highfield unravel the mind-bending possibilities of digital twins in their new book. #Virtual You  Are you ready to digitally clone your health for the benefits of precision medicine? There are mind-bending opportunities, but also risks to consider.

Are you ready to see the future of healthcare? Discover how brain computer interfaces are transforming the medical landscape in the next episode of The Futurist. What could this mean for the future of human potential? Stay tuned to find out - only on the Medtronic YouTube channel.

🎉 New paper on #causalML at #ICML2024: "𝐌𝐞𝐭𝐚-𝐋𝐞𝐚𝐫𝐧𝐞𝐫𝐬 𝐟𝐨𝐫 𝐏𝐚𝐫𝐭𝐢𝐚𝐥𝐥𝐲-𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐢𝐞𝐝 𝐓𝐫𝐞𝐚𝐭𝐦𝐞𝐧𝐭 𝐄𝐟𝐟𝐞𝐜𝐭𝐬 𝐀𝐜𝐫𝐨𝐬𝐬 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐄𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬" 👉 We aim to estimate #treatment #effects from #multiple #hospitals ✋ The naive way is simply to concatenate data and then estimate the treatment effects. But, we show that there is a more clever way. 💡 The clue: #overlap and #unconfoundedness cancel each out. For example, a hospital with a fully deterministic treatment assignment has zero overlap but also zero unconfoundedness 👌 This allows us to derive #bounds for more precise estimates. Link: https://lnkd.in/dP2MiSgT with Jonas Schweisthal Dennis Frauen Mihaela van der Schaar Munich Center for Machine Learning

#IJCAI2024 At the Survey Track, MTA: Multidisciplinary Topics and Applications session with a #talk AI-Enhanced Virtual Reality in Medicine: A Comprehensive Survey by Yixuan Wu, Kaiyuan Hu, Danny Z. Chen, Jian Wu

#SmartHealthcare #AI #ML #CNN #SVM #2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN) #IEEE Dear connections, one of our work "A Machine Learning Approach to Predict NICU Units in Hospital by Developing Smart e-Healthcare System " published in 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN) of IEEE. Visit the link : https://lnkd.in/gPzkHVQc

AI today, and quantum computing over the next 5+ years offers the greatest technological advancements to personalize medicine and improve patient health outcomes at scale. We're just at the beginning of this unprecedented journey. I invite you to booth 2661 at HIMSS to learn more about this journey and where it will be taking our health.

Hot off the press! 🗞️ The latest edition of The Memo, featuring Filip Peters CEO of Acorai, is out now. Here’s a preview of this week’s edition of our weekly newsletter, The Memo: The best ideas often come from cross-pollination between industries. In the case of Filip Peters, CEO and Co-Founder of Acorai, it was applications of machine learning in the financial sector that sparked Acorai’s founding to tackle unmet needs in healthcare. "My background is in machine learning," Peters explains. "I was working in finance and seeing advanced techniques being used in time series data, and I thought that this should be possible to apply to different fields.” With his expertise and passion for computers and hardware, Peters began exploring spaces within healthcare where machine learning was poised to have the biggest impact. "We looked at various possibilities and ultimately focused on heart failure due to the immense unmet need and the promising commercial case," Peters explains. "Heart failure affects over 60 million patients worldwide. We saw a significant opportunity to address this worldwide issue." Continue Reading: https://lnkd.in/gauCkYir

 As these AI systems become more accurate, it’s inevitable that our government will ban them for “our safety” once the Medical Industrial Complex catches wind. If a medical professional brow-beats you for “doing your own research” with one of these tools in the future, remind them that in the United States, 210k-440k people die and 10-20X more are seriously injured annually from medical errors perpetrated by their industry. Even Meteorologists have to cringe at those stats. If you are interested in augmenting your medical research with AI, check out “Health-LLM”. It tested 83.3% accurate in diagnosis across a small 61 disease dataset (there are 17,000 diagnosis codes possible). I can’t wait to (carefully & responsibly) experiment with this when it becomes publicly available. Health-LLM News: https://lnkd.in/gqkG5jBP USA Medical Error Stats: https://lnkd.in/gGHj4Kav