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Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials
This paper proposes algorithm fidelity as a critical requirement for deploying online RL algorithms in clinical trials.
Early Prediction of Geomagnetic Storms by Machine Learning Algorithms
Given that important predictive features such as historic Kp indices are measured every 3 hours and their importance decay quickly with the amount of time in advance, an early prediction of 3 hours ahead of time is believed to be close to the practical limit.
Automatically Score Tissue Images Like a Pathologist by Transfer Learning
The proposed algorithm has made it possible to break the critical accuracy barrier (the 75% accuracy level of pathologists), with a reported accuracy of 75. 9% on breast cancer TMA images from the Stanford Tissue Microarray Database.
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