Case Study: Northwestern Medicine improves follow-up care and operational efficiency with Weights & Biases

Northwestern Medicine Delivers Timely and Quality Care with W&B

Northwestern Medicine, an academic medical center, faced the challenge of missed and delayed patient follow-up care due to the difficulty of tracking recommendations buried in lengthy radiology reports. To improve outcomes, they partnered with Weights & Biases to build their first deep learning project: an NLP system to automatically identify findings that required follow-up.

Using the Weights & Biases platform to track experiments and optimize system resources, the team developed and integrated an AI tool with their Epic electronic health records. The solution has screened hundreds of reports daily, generating nearly 5,000 physician interactions and tracking over 2,400 follow-ups to completion, ultimately helping to ensure timely care and save lives.

Northwestern Medicine

Mozzi Etemadi

Anesthesiologist and Director of Advanced Technologies