ChatGPT in Medicine by MEDIROBOT

https://youtu.be/rKV5JcALQoQ?si=nh3d6Av4qtZs8HHU

https://www.anthropic.com/news/fable-mythos-access

https://youtu.be/GUEE9OA4keo?si=-QU52OkqFMRBM_nL

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🎁The AI Leap Nobody Was Ready For 👇 https://www.oneusefulthing.org/p/what-it-feels-like-to-work-with-mythos?r=i5f7&utm_campaign=post&utm_medium=web&triedRedirect=true ▶️For context 👇 https://en.wikipedia.org/wiki/Claude_Mythos

https://youtu.be/ZN0gkZw-2ks?si=T2aiD_bsOueXRhMH

ChatGPT in Medicine by MEDIROBOT pinned «45. Science skills in Google Antigravity. The new Science Skills bundle allows researchers to run complex workflows like protein analysis in minutes using specialized Alpha* models and 30+ major scientific databases. 👇 https://x.com/antigravity/status/2…»

45. Science skills in Google Antigravity. The new Science Skills bundle allows researchers to run complex workflows like protein analysis in minutes using specialized Alpha* models and 30+ major scientific databases. 👇 https://x.com/antigravity/status/2061519617550340492?s=20 https://github.com/google-deepmind/science-skills 🤔 How does a clinical radiologist ACTUALLY use this? This is NOT a PACS integration or an image-reading AI. Instead, think of it as your ultimate, hyper-intelligent MDT (Tumor Board) coordinator and diagnostic detective for complex cases. It handles the genetics, pharmacology, and literature so you can focus on the imaging. 📂 WHAT FILES CAN YOU UPLOAD?   - PDFs/Text: Genetic sequencing reports, clinical encounter notes, pathology     reports.   - CSVs/Excel: Patient medication lists, lab results, or your own research datasets. 🗣 REAL-WORLD RADIOLOGY USE CASES & PROMPTS 🚨 Scenario 1: The "Weird Pattern" & Drug Toxicity You are reading an HRCT and see a crazy pattern of organizing pneumonia or interstitial fibrosis. The patient is on 15 different medications.   - You Upload: A text file or CSV of the patient’s medication list.   - Your Prompt: "I am seeing an unusual pattern of organizing pneumonia on this     patient's HRCT. Here is their medication list. Please use the OpenFDA skill     to query adverse event reports for all these drugs. Tell me which ones have     the highest statistically reported incidence of 'pneumonitis' or     'interstitial lung disease', and summarize the findings."   - How it answers: The AI will write a Python script in the background, query     the OpenFDA database for every drug, analyze the adverse event JSON data,     and output a clean table showing you exactly which drug is the likely     culprit. 🧬 Scenario 2: Pediatric/Neuro/MSK Rare Genetics You are reading a pediatric whole-body MRI for suspected congenital muscular dystrophy, or a brain MRI for a leukodystrophy. The clinical notes include a newly discovered genetic variant, but you don't know if it matches the imaging phenotype.   - You Upload: The PDF of the geneticist's report.   - Your Prompt: "The report shows a variant at chr21:46126238:G>C in the COL6A2 gene. Use the AlphaGenome and ClinVar skills to analyze this variant. Does it cause a significant functional disruption (like exon skipping)? Summarize if the molecular mechanism correlates with the connective tissue/muscular     dystrophy pattern I am seeing."   - How it answers: It will run an AlphaGenome single-variant analysis. (Fun fact: the AI actually generates real plots showing splice donor disruptions!). It will tell you if the variant is likely benign or pathogenic, helping you suggest genotype-phenotype correlation in your dictation. 📚 Scenario 3: Tumor Board (MDT) Prep & Protocoling You are presenting a complex oncology case at Tumor Board. The patient is on a brand new targeted therapy, and you need to know if the new liver lesions are metastasis or a known drug effect (pseudoprogression).   - Your Prompt: "Search PubMed and OpenAlex for the latest clinical trials     (2024-2026) regarding MRI response patterns in hepatocellular carcinoma     treated with [Specific Immunotherapy]. Use the fetch tool to download the     abstracts and full PDFs if open-access. Summarize the imaging pitfalls,     specifically looking for rates of pseudoprogression."   - How it answers: The agent will autonomously query PubMed using advanced MeSH     tags, download the relevant papers, read them, and give you a bulleted     summary with proper citations (e.g., [1], [2]) that you can literally     copy-paste into your Tumor Board slides. ▶️ When you ask these questions, Antigravity doesn't just "guess" like ChatGPT usually does. It physically executes the bundled uv Python scripts (like openfda_query.py or search_pubmed.py), pulls the raw scientific data from the servers, reads it, and formats it for you. ▶️For more context regarding these things 👇 https://youtu.be/QvN6Tu6dHYM?si=qB_Siaakjgq4hh_G

https://youtu.be/QvN6Tu6dHYM?si=F37u9yjUB7RIbrHd

Demis Hassabis on the limit in today’s AI: language can describe the world, but it cannot contain it - and why "World Models" are his "longest standing passion". Language models absorbed far more structure about reality from text than many researchers expected, because human language quietly carries physics, psychology, culture, tools, plans, and cause-and-effect. But text is still a compressed residue of experience, not experience itself. A sentence can say a cup falls from a table, yet it does not fully encode weight, grip, balance, friction, timing, sound, surprise, or the tiny motor corrections a body makes before it even notices them. The world is not only made of facts that can be named; it is made of constraints that have to be lived through, touched, predicted, violated, and repaired. That is why world models matter. They aim to learn the hidden grammar of physical reality: how objects persist, how forces unfold, how space changes when an agent moves, and how action creates feedback. Language models can often reason about the world because people have written so much about it. World models try to learn what the world is like before it becomes words. The difference is exactly what matters because intelligence is not just answering well; it is knowing what would happen next if you moved, reached, pushed, smelled, slipped, or failed. A mind trained only on descriptions may become brilliant at explanation. A mind trained on experience may become better at consequence. --- Full video https://youtu.be/PqVbypvxDto?si=LeJhlDiT2wdwAQ3E

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https://youtu.be/ZqRtR6Z2U6U?si=f5XdegSiRE7e8dAh