👁️8,962
GitHubLinkedIn
AI in Healthcare and Science2 min read341 words

🤖 AI/ML - Molecular Representation Fine-tuning

👁️0reads (human + AI)🤖0AI ingestions

🤖 AI/ML - Molecular Representation Fine-tuning

This article describes how pretrained molecular representations offer a practical signal for reactive fine-tuning of machine learning interatomic potentials (MLIPs) at scale.

Key Points:
• Pretrained molecular representations provide an acquisition signal.

• This signal is self-contained and practical.

• It supports reactive MLIP fine-tuning at scale.

🔗 Resources:
Research Paper ↗ - Paper on molecular representation fine-tuning


🚀 Scientific Collaboration - OpenLabs Platform

This article introduces OpenLabs, a collaborative science platform designed for open participation by both humans and AI agents. It facilitates posting, discussing, and developing scientific hypotheses.

Key Points:
• OpenLabs serves as a public posting layer for science.

• Both humans and AI agents can participate collaboratively.

• The platform supports open discussion and hypothesis development.

🔗 Resources:
BioProtocol ↗ - Information about the OpenLabs platform

Image

Image


✨ OpenMed - On-Device Medical AI Updates

This article details recent updates for the OpenMed project, highlighting new technical capabilities and expanded support for medical domains and languages.

Key Points:
• De-identification now runs in-browser using wasm and WebGPU.

• Offline support is available for Android devices via React Native.

• New domains include endocrinology, anesthesia, and genomics.

• Danish, Filipino, and Malay languages are now supported.

🔗 Resources:
OpenMed AI ↗ - On-device medical AI project updates

Image

Image


🤖 AI Applications - Immunotherapy Responder Prediction

This article discusses an AI model designed to improve the prediction of immunotherapy responders. The model uses tumor gene activity to identify patients who may benefit from treatment and provides explanations for its predictions.

Key Points:
• An AI model enhanced immunotherapy responder prediction by 8.5%.

• It identifies potential beneficiaries prior to treatment.

• The model provides explanations based on tumor gene activity.

🔗 Resources:
Medical Xpress Article ↗ - AI model for immunotherapy prediction


⭐️ Support

If you liked reading this report, please star ⭐️ this repository and follow me on Github ↗, 𝕏 (previously known as Twitter) ↗ to help others discover these resources and regular updates.


Related AI in Healthcare and Science Breakdowns

Drix10
Written by Drix10

Co founder @ PartPilot | 1 x Acquired Founder | Canopy @ f.inc | Cybersec @ DSU | 2x International Hackathon 🏆. Read more on drix10.com.