MLHC 2016

19 papers

A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves Yanbo Xu, Yanxun Xu, Suchi Saria

Clinical Tagging with Joint Probabilistic Models Yoni Halpern, Steven Horng, David Sontag

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

Deep Survival Analysis Rajesh Ranganath, Adler Perotte, Noémie Elhadad, David Blei

Diagnostic Prediction Using Discomfort Drawings with IBTM Cheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo Bertilson

Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time Series Zachary C Lipton, David Kale, Randall Wetzel

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun

gLOP: The Global and Local Penalty for Capturing Predictive Heterogeneity Rhiannon Rose, Daniel Lizotte

Identifiable Phenotyping Using Constrained Non-Negative Matrix Factorization Shalmali Joshi, Suriya Gunasekar, David Sontag, Ghosh Joydeep

Input-Output Non-Linear Dynamical Systems Applied to Physiological Condition Monitoring Konstantinos Georgatzis, Chris Williams, Christopher Hawthorne

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

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

Multi-Task Prediction of Disease Onsets from Longitudinal Laboratory Tests Narges Razavian, Jake Marcus, David Sontag

Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical Data Joseph Futoma, Mark Sendak, Blake Cameron, Katherine Heller

Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional Data Truyen Tran, Wei Luo, Dinh Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh

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

Uncovering Voice Misuse Using Symbolic Mismatch Marzyeh Ghassemi, Zeeshan Syed, Daryush Mehta, Jarrad Van Stan, Robert Hillman, John Guttag

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