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AI and Pathology: Steering Treatment and Predicting Outcomes

arXiv 2206.07573 ↗First posted 15 Jun 2022cs.AI q-bio.QM q-bio.TOcited by 0

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Abstract (arXiv)

The combination of data analysis methods, increasing computing capacity, and improved sensors enable quantitative granular, multi-scale, cell-based analyses. We describe the rich set of application challenges related to tissue interpretation and survey AI methods currently used to address these challenges. We focus on a particular class of targeted human tissue analysis - histopathology - aimed at quantitative characterization of disease state, patient outcome prediction and treatment steering.

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