AI and Pathology: Steering Treatment and Predicting Outcomes

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 chal...

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Hauptverfasser: Gupta, Rajarsi, Kaczmarzyk, Jakub, Kobayashi, Soma, Kurc, Tahsin, Saltz, Joel
Format: Artikel
Sprache:eng
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Zusammenfassung: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.
DOI:10.48550/arxiv.2206.07573