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Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?

, , , , , , , , , and . ML4H@NeurIPS, volume 116 of Proceedings of Machine Learning Research, page 1-9. PMLR, (2019)

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Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes., , , , , , and . AISTATS, volume 108 of Proceedings of Machine Learning Research, page 4045-4055. PMLR, (2020)Performance drift in a mortality prediction algorithm among patients with cancer during the SARS-CoV-2 pandemic., , , , , , , and . J. Am. Medical Informatics Assoc., 30 (2): 348-354 (January 2023)Using Whole Slide Image Representations from Self-Supervised Contrastive Learning for Melanoma Concordance Regression., , , , , , , and . CoRR, (2022)A Reinforcement Learning Approach to Weaning of Mechanical Ventilation in Intensive Care Units., , , , and . UAI, AUAI Press, (2017)Machine Learning for Health (ML4H) Workshop at NeurIPS 2018., , , , , , , , , and 8 other author(s). CoRR, (2018)Monitoring Performance of a Deployed Machine Learning Model that Predicts Long-term Mortality for Targeting Inpatient Palliative Care., , , , , and . AMIA, AMIA, (2022)Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes., , , , , , and . CoRR, (2019)Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?, , , , , , , , , and . ML4H@NeurIPS, volume 116 of Proceedings of Machine Learning Research, page 1-9. PMLR, (2019)Using Whole Slide Image Representations from Self-supervised Contrastive Learning for Melanoma Concordance Regression., , , , , , , , and . ECCV Workshops (7), volume 13807 of Lecture Notes in Computer Science, page 442-456. Springer, (2022)Sparse multi-output Gaussian processes for online medical time series prediction., , , , , , and . BMC Medical Informatics Decis. Mak., 20 (1): 152 (2020)