Our recent interview with UW News highlights why transparency in medical AI is vital for patient safety. Please check it out! 👇

Allen School@uwcse.bsky.social · last yr.

Medical #AI errors “can directly impact people’s health and even determine life-altering outcomes.” In @natrevbioeng.nature.com, @chanwoo-kim.bsky.social @sohamgadgil.bsky.social & @suinlee.bsky.social discuss the importance of transparency in medical models. www.washington.edu/news/2025/09...

AI models are being applied more often across a range of biomedical domains to support clinical decision-making and therapeutic strategies. A Review in Nature Reviews Bioengineering examines the transparency of medical AI systems, highlighting key approaches to increasing transparency. 🔒

Transparency of medical artificial intelligence systems - Nature Reviews Bioengineering

Artificial intelligence (AI) models are being applied more often across a range of biomedical domains to support clinical decision-making and therapeutic strategies. This Review examines the transparency of medical AI systems, highlighting key approaches to increasing transparency in model design, operation and outcomes.

go.nature.com

🚀 We’re at the tipping point of the AI era, and nowhere is its potential more profound than in medicine 💉🧬. But with great promise comes great responsibility. That is, ensuring transparency and safety of medical AI is crucial to its successful adoption. This is where our paper comes in.

I'm hiring: 1. Research associate (wet-lab w/ phd) to generate mpra perturbation data 2. ML postdoc to build multimodal generative AI for DNA (eg diffusion and LLMs) 3. Bioinformatician (any level) to process and harmonize functional genomics data to train foundation models DM me if interested!