Podcasts links:
Youtube : youtu.be/SbFp4fnuxjo
Spotify : open.spotify.com/episode/6s13...
#medical-ai #healthcare #research #llms
@openlifesciai.bsky.social
Daily tweets: Latest Medical LLMs, Datasets, Benchmarks, and Top Research Papers ⚡ Life Science AI https://youtube.com/@OpenlifesciAI
Podcasts links:
Youtube : youtu.be/SbFp4fnuxjo
Spotify : open.spotify.com/episode/6s13...
#medical-ai #healthcare #research #llms
🔬 Special Focus: Medical Ethics & AI
- Clinical Trust Impact Study
- Mental Health AI Challenges
- Hospital Monitoring Ethics
- Radiology AI Integration
💻 LLM Applications
- Patient-Friendly Video Reports
- Medical Video QA Systems
- Gene Ontology Annotation
- Healthcare Recommendations
📊 Benchmarks & Evaluations
> Multi-OphthaLingua
- Multilingual ophthalmology benchmark
- Focus on LMICs healthcare
- Bias assessment framework
- ACE-M3 Evaluation Framework
- Multimodal medical model testing
- Comprehensive capability assessment
- Standardized evaluation metrics
🔧 Frameworks & Methods
- ReflecTool: Reflection-Aware Clinical Agents
- Process-Supervised Clinical Notes
- Federated Learning with RAG
- Query Pipeline Optimization
🤖 Medical LLM & Other Models
- MedMax: Mixed-Modal Biomedical Assistant
- Advanced multimodal instruction tuning
- Enhanced biomedical knowledge integration
- Comprehensive assistant capabilities
Last Week in Medical AI: Top Research Papers/Models 🔥
🏅 (December 15 - December 21, 2024)
Full thread in detail: x.com/OpenlifesciA...
Youtube Link: www.youtube.com/watch?v=SbFp...
Spotify: t.co/QPmdrXuWP9
5/5 For daily insights into Medical AI breakthroughs:
💬 Discord: discord.gg/A5Fjf5zC69
📺 YouTube: youtube.com/@OpenlifesciAI
🎧 Spotify: open.spotify.com/show/4edRuST...
4/5 Key Models in HAI-DEF
• CXR Foundation: Models like ELIXR-C & ELIXR-B excel in chest radiography tasks.
• Path Foundation: ViT-based models for stain-agnostic histopathology image analysis.
• Derm Foundation: BiT ResNet models for diverse dermatology tasks.
3/5 Why HAI-DEF Matters
Building robust medical AI is costly and data-intensive. HAI-DEF:
- Speeds up development with pre-trained models.
- Overcomes data scarcity for rare conditions.
- Reduces computing needs.
2/5 HAI-DEF provides:
- Pre-trained foundation models for X-rays, CT, histopathology, dermatology, & audio.
- Compact embeddings requiring less labeled data, reducing training times and costs.
- Open-source tools and research endpoints for easy integration.
How can pre-trained foundation models transform healthcare?
@GoogleAI introduces Health AI Developer Foundations (HAI-DEF), a suite of domain-specific tools and models for diverse medical modalities!
Here’s what you need to know: 👇🧵 1/5
It's encouraging to see tech companies like Google, Microsoft, and OpenAI, have already adopted our benchmarks to evaluate their models. 🔥
Exciting news! 📢 In collaboration with Hugging Face 🤗, we are launching the Medical-LLM Leaderboard. This leaderboard aims to evaluate large language models in the medical domain.
huggingface.co/blog/leaderb...
For my fellow researchers in AI, Medical, and Healthcare domain:, Here is the Medical AI Startup pack if you are new there
go.bsky.app/PddA2uy