English

AI and Pathology: Steering Treatment and Predicting Outcomes

Artificial Intelligence 2022-06-16 v1 Quantitative Methods Tissues and Organs

Abstract

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.

Keywords

Cite

@article{arxiv.2206.07573,
  title  = {AI and Pathology: Steering Treatment and Predicting Outcomes},
  author = {Rajarsi Gupta and Jakub Kaczmarzyk and Soma Kobayashi and Tahsin Kurc and Joel Saltz},
  journal= {arXiv preprint arXiv:2206.07573},
  year   = {2022}
}