Inventors:
- Mountain View CA, US
Shravya Ramash Shetty - San Francisco CA, US
Siddhant Mittal - New York NY, US
David Francis Steiner - Redwood City CA, US
Anna Majkowska - San Francisco CA, US
Gavin Elliott Duggan - Mountain View CA, US
International Classification:
G16H 50/20
G16H 30/20
Abstract:
The present disclosure provides systems and methods for training and/or employing machine-learned models (e.g., artificial neural networks) to diagnose chest conditions such as, as examples, pneumothorax, opacity, nodules or masses, and/or fractures based on chest radiographs. For example, one or more machine-learned models can receive and process a chest radiograph to generate an output. The output can indicate, for each of one or more chest conditions, whether the chest radiograph depicts the chest conditions (e.g., with some measure of confidence). The output of the machine-learned models can be provided to a medical professional and/or patient for use in providing treatment to the patient (e.g., to treat a detected condition).