Seeing the random forest through the decision trees. Supporting learning
  health systems from histopathology with machine learning models: Challenges
  and opportunities
Ricardo Gonzalez Ashirbani Saha Clinton J. V. Campbell Peyman Nejat Cynthia Lokker Andrew P. Norgan
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.