Foundation models, advanced artificial intelligence systems trained on large-scale datasets, hold the potential to provide unprecedented advancements for the medical field.
Mar 19 2024Mass General Brigham In computational pathology , these models may excel in diagnostic accuracy, prognostic insights, and predicting therapeutic responses. Researchers at Mass General Brigham have designed the two of the largest CPath foundation models to date: UNI and CONCH. These foundation models were adapted to over 30 clinical, diagnostic needs, including disease detection, disease diagnosis, organ transplant assessment, and rare disease analysis.
CONCH is a foundation model for understanding both pathology images and language. Trained on a database of over 1.17 million histopathology image-text pairs, CONCH excels in tasks like identifying rare diseases, tumor segmentation, and understanding gigapixel images. Because CONCH is trained on text, pathologists can interact with the model to search for morphologies of interest.
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