Chanwoo Kim

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

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.

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. 🔒

Here's a SharedIt link (no license required): rdcu.be/eFnIc

Grateful to the amazing team @sohamgadgil.bsky.social @suinlee.bsky.social @uwcse.bsky.social who made this possible!
Many thanks to the editorial team Christine Horejs for positive and constructive feedback!

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 transpare...

We hope this becomes a valuable resource for many in the field, including researchers, clinicians, developers, and policymakers, dedicated to building responsible and trustworthy AI in healthcare.

📖 Read our full paper here: doi.org/10.1038/s442...

🔍 In this work, we cover:
🔹 Methods to enhance transparency across the entire AI lifecycle—from data collection 📊 to model development ⚙️ to clinical deployment 🏥.
🔹 Regulations on transparency that will influence its trajectory ⚖️
🔹 Insights into the evolving landscape of medical AI transparency 📈

Transparency of medical artificial intelligence systems

📣 Excited to announce that our review article “Transparency of Medical Artificial Intelligence Systems,” has just been published in Nature Reviews Bioengineering!

🚀 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!