AI researcher · Palo Alto
I work in radiology AI to help radiologists save time.
Lead or senior author in Nature, Nature Medicine, Nature Biomedical Engineering, ACL, EMNLP, NeurIPS and ICLR.
Long-form reading notes on radiology AI papers, with a focus on report generation.
A MICCAI 2025 paper labels 800 cardiac MRI, CTPA, head CT and ultrasound reports and tests the released RadGraph extractors on them. What a fine-tuned extractor gains, what the comparison can and can't say, and what it means for scoring CT and MRI reports with RadGraph-F1.
CoCa-CXR is built to write what changed since the last chest X-ray, yet its RadGraph F1 is no higher with those comparison sentences. What its report score, its copied baselines and its progression benchmark can and can't show.
MedGemma, Google's open medical vision-language model, writes chest X-ray reports; its best RadGraph F1 in Nature Medicine is 30.3. Where that number comes from, what the comparison rows were measured on, and what the reader study shows.
