Volume 56: Machine Learning for Healthcare Conference, 18-19 August 2016, Northeastern University, Boston, MA, USA

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

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

Konstantinos Georgatzis, Chris Williams, Christopher Hawthorne ; PMLR 56:1-16

Identifiable Phenotyping using Constrained Non-Negative Matrix Factorization

Shalmali Joshi, Suriya Gunasekar, David Sontag, Ghosh Joydeep ; PMLR 56:17-41

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data

Joseph Futoma, Mark Sendak, Blake Cameron, Katherine Heller ; PMLR 56:42-54

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 ; PMLR 56:55-72

Multi-task Prediction of Disease Onsets from Longitudinal Laboratory Tests

Narges Razavian, Jake Marcus, David Sontag ; PMLR 56:73-100

Deep Survival Analysis

Rajesh Ranganath, Adler Perotte, Noémie Elhadad, David Blei ; PMLR 56:101-114

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 ; PMLR 56:115-133

gLOP: the global and Local Penalty for Capturing Predictive Heterogeneity

Rhiannon Rose, Daniel Lizotte ; PMLR 56:134-149

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 ; PMLR 56:150-163

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

Truyen Tran, Wei Luo, Dinh Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh ; PMLR 56:164-177

Learning Robust Features using Deep Learning for Automatic Seizure Detection

Pierre Thodoroff, Joelle Pineau, Andrew Lim ; PMLR 56:178-190

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 ; PMLR 56:191-208

Clinical Tagging with Joint Probabilistic Models

Yoni Halpern, Steven Horng, David Sontag ; PMLR 56:209-225

Diagnostic Prediction Using Discomfort Drawings with IBTM

Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo Bertilson ; PMLR 56:226-238

Uncovering Voice Misuse Using Symbolic Mismatch

Marzyeh Ghassemi, Zeeshan Syed, Daryush Mehta, Jarrad Van Stan, Robert Hillman, John Guttag ; PMLR 56:239-252

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

Zachary C Lipton, David Kale, Randall Wetzel ; PMLR 56:253-270

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 ; PMLR 56:271-281

A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves

Yanbo Xu, Yanxun Xu, Suchi Saria ; PMLR 56:282-300

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks

Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun ; PMLR 56:301-318

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