Section outline

    1. Jenna Wiens, John Guttag, Eric Horvitz, Patient Risk Stratification with Time-Varying Parameters: A Multitask Learning Approach, JMLR 2016, PDF
    2. Tim Smolem et atl, A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy, Computers in Biology and Medicine, 2021, PDF
    3. Ping Wang, Yan Li, and Chandan K. Reddy. 2019. Machine Learning for Survival Analysis: A Survey. ACM Comput. Surv. 51, 6, Article 110, 2019, Arxiv
    4. David G. Kleinbaum , Mitchel Klein, Survival Analysis, A Self-Learning Text, 2005, Online
    5. Dimitris Bertsimas,  Jack Dunn, Emma Gibson, Agni Orfanoudak, Machine learning, 2022, PDF
    6. S. Chen, W. Guo, Auto-Encoders in Deep Learning—A Review with New Perspectives, Mathematics, 2023, Online
    7. D. Pratella et al,  A Survey of Autoencoder Algorithms to Pave the Diagnosis of Rare Diseases, Int. J. Mol. Sci.. 2021, Online
    8. Jan Ehrhardt, Matthias Wilms, Autoencoders and variational autoencoders in medical image analysis, MICCAI Society book Series, Online
    9. Manuel Cossio, Augmenting Medical Imaging: A Comprehensive Catalogue of 65 Techniques for Enhanced Data Analysis, 2023, Arxiv
    10. Pooya Mobadersany et al, Predicting cancer outcomes from histology and genomics using convolutional networks, PNAS 2017, Online
    11. Jun ma et al, Segment anything in medical images, Nature 2024, Online