Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities
Computer Vision and Pattern Recognition2023-12-08v1
This paper discusses some overlooked challenges faced when working with machine learning models for histopathology and presents a novel opportunity to support "Learning Health Systems" with them. Initially, the authors elaborate on these challenges after separating them according to their mitigation strategies: those that need innovative approaches, time, or future technological capabilities and those that require a conceptual reappraisal from a critical perspective. Then, a novel opportunity to support "Learning Health Systems" by integrating hidden information extracted by ML models from digitalized histopathology slides with other healthcare big data is presented.
@article{arxiv.2312.03812,
title = {Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities},
author = {Ricardo Gonzalez and Ashirbani Saha and Clinton J. V. Campbell and Peyman Nejat and Cynthia Lokker and Andrew P. Norgan},
journal= {arXiv preprint arXiv:2312.03812},
year = {2023}
}