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JMLR Workshop and Conference Proceedings

Volume 56: Proceedings of the 1st Machine Learning for Healthcare Conference

Editors: Finale Doshi-Velez, Jim Fackler, David Kale, Byron Wallace, Jenna Weins

Contents:

Accepted Papers

Input-Output Non-Linear Dynamical Systems applied to Physiological Condition Monitoring

Konstantinos Georgatzis, Chris Williams, Christopher Hawthorne

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization

Shalmali Joshi, Suriya Gunasekar, David Sontag, Ghosh Joydeep

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data

Joseph Futoma, Mark Sendak, Blake Cameron, Katherine Heller

Using Kernel Methods and Model Selection for Prediction of Preterm Birth

Ilia Vovsha, Ansaf Salleb-Aouissi, Anita Raja, Thomas Koch, Alex Rybchuk, Axinia Radeva, Ashwath Rajan, Yiwen, Huang, Hatim Diab, Ashish Tomar, Ronald Wapner

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests

Narges Razavian, Jake Marcus, David Sontag

Deep Survival Analysis

Rajesh Ranganath, Adler Perotte, Noémie Elhadad, ,David Blei

Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy

Bilal Ahmed, Thomas Thesen, Karen Blackmon, Ruben Kuzniecky, Orrin Devinsky, Jennifer Dy, Carla Brodley

gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity

Rhiannon Rose, Daniel Lizotte

Transferring Knowledge from Text to Predict Disease Onset

Yun Liu, Collin Stultz, John Guttag, Kun-Ta Chuang, Kun-Ta Chuang, Fu-Wen Liang, Huey-Jen Su

Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data

Truyen Tran, Wei Luo, Dinh Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh

Learning Robust Features using Deep Learning for Automatic Seizure Detection

Pierre Thodoroff, Joelle Pineau, Andrew Lim

Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature Representations

Peter J. Schüffler, Judy Sarungbam, Hassan Muhammad, Ed Reznik, Satish Tickoo, Thomas Fuchs

Clinical Tagging with Joint Probabilistic Models

Yoni Halpern, Steven Horng, David Sontag

Diagnostic Prediction Using Discomfort Drawings with IBTM

Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo Bertilson

Uncovering Voice Misuse Using Symbolic Mismatch

Marzyeh Ghassemi, Zeeshan Syed, Daryush Mehta, Jarrad Van Stan, Robert Hillman, John Guttag

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series

Zachary C Lipton, David Kale, Randall Wetzel

Deep Convolutional Neural Networks for Microscopy-Based Point of Care Diagnostics

John A Quinn, Rose Nakasi, Pius K. B. Mugagga, Patrick Byanyima, William Lubega, Alfred Andama

A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time Series

Yanbo Xu, Yanxun Xu, Suchi Saria

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun