Modern Hygienist’s Post

Know how AI can assist in Medical Image analysis. SUBSCRIBE OUR NEW YOUTUBE CHANNEL: https://lnkd.in/gvd5mhsu #artificialintelligence #aifacts #ai #dailyaifacts #aifactsdaily #didyouknow #didyouknowfacts

Why is Image Recognition a Key Function of AI? Humans are visual, and AI is designed to emulate human brains. Therefore, teaching machines to recognize and categorize images is a crucial part of AI. Image recognition also helps machines to learn because the more images that are processed, the better the software gets at recognizing and processing those images.

Insights from the present and future of AI: Advancements in performance, ethical considerations, higher education's role in AI education, AI's impact on healthcare, and the importance of AI accountability. Stay updated on the evolving AI landscape! [Link to the article: https://lnkd.in/eiFMptwB] #HospitalityIndustry #CEOPerspectives #Innovation #Safety #PersonalizedService #AI #Innovative #StaffProWorkforceSolutions

🤖 Understand AI's brain: Explainable Artificial Intelligence is key to unraveling "Blackbox" Deep Learning. It builds trust by demystifying AI decisions. Vital in Medical Imaging, Business, AI ethics, and making AI accessible. Its the future of how we can interact with AI🔍🌟 #explainableai #machinelearning #artificialintelligence

Neuro AI. Will it be the future in AI and overcome the LLM limitations? Interview with Dr. Gabriele Scheler. She also answered these questions: - Is AGI close with current LLMs? - Can the current AI threaten humanity? - Will self-driving cars be here within the next 5 years? - Will AI cost lots of jobs and could that lead to a big societal problem? - Can AI be regulated by the companies who profit from it? - Is Neuralink something that will lead to useful applications? https://lnkd.in/dx-FqEPs

Feel good Sunday: How to keep AI under control With the rapid advancement of AI #technology, there is a growing concern about the potential dangers of superintelligent AI. However, scientist Max Tegmark offers an optimistic outlook on how we can ensure AI works for us, not against us. But what if the #AI can't create the necessary tools on its own? Tegmark suggests training one AI to learn your desired tasks and then using another AI to extract the learned algorithm and knowledge, similar to an AI #neuroscientist. This approach aligns with the progress being made in mechanistic interpretability, showing that creating safe AI systems is within reach. For more insights on controlling AI, check out Max Tegmark's TED talk: https://lnkd.in/dqMNKQ75 #Loquat

Come to our #AI seminar tomorrow! Jeff Hancock is the Harry and Norman Chandler Professor of Communication at Stanford University. At this seminar, Hancock will cover recent research on how people perceive and detect AI in human communication, and how generative AI will likely undermine trust in several important human domains. Join us on zoom here: bit.ly/45HVRWt #ArtificialIntelligence #research #communication

"The ability to accurately assess the validity, reproducibility, & clinical applicability of artificial intelligence (AI) studies is crucial for anyone interested in AI in Imaging" https://lnkd.in/gMdfq9hk 10 key factors to examine clinical AI publications: study purpose, function & clinical context of AI, training data, data preprocessing, AI modeling techniques, test data, AI performance, helpfulness & value of AI, interpretability of AI, & code sharing.

This image from a children book has finally given me the best explanation why #AI will never replace #pathologists. Can you guess what it is? In order to train a #computationalpathology model, the challenge is to single out 3D objects on a 2D image. This means, countless angles which will give the objects a different shape on the image and possibly additional other alterations, like overlaying objects or cut-offs. When I read the children’s book ‘Good night, Gorilla’ to my not yet two year old daughter, she had no problem to point out the moon in this image, even though it is not fully depicted. This is because, humans (and even very young ones) understand the context of the image. My daughter knows that the moon is at the sky, she knows it is usually best seen at night and she can complement the shape in her head because the image is just a snapshot of something larger. Now, imagine how many examples would need to be fed into an AI model to come to the same conclusion and how likely it is, that one of the angles/conditions were not part of the training. Whilst AI has virtues in tasks like #quantification and #featureextraction, the abstract thinking and the background knowledge will not be replaceable. The skill sets are complementary and AI is and will be a great asset to pathologists. What is your opinion?

Multi-modal AI is going to really shake things up! AI isn't replacing a radiologist anytime in the immediate future. We still need humans in the loops, but it will soon make their jobs much easier for the routine cases, including the drudgery of report paperwork! It may even help call out things that aren't obvious. With a little more time and training, AI can improve medicine even more, and that's a good thing! #AI #GenerativeAI #ArtificialIntelligence