Abstract is missing.
- Input-Output Non-Linear Dynamical Systems applied to Physiological Condition MonitoringKonstantinos Georgatzis, Christopher K. I. Williams, Christopher Hawthorne. 1-16 [doi]
- Identifiable Phenotyping using Constrained Non-Negative Matrix FactorizationShalmali Joshi, Suriya Gunasekar, David Sontag, Joydeep Ghosh. 17-41 [doi]
- Predicting Disease Progression with a Model for Multivariate Longitudinal Clinical DataJoseph Futoma, Mark Sendak, Blake Cameron, Katherine A. Heller. 42-54 [doi]
- Using Kernel Methods and Model Selection for Prediction of Preterm BirthIlia Vovsha, Ansaf Salleb-Aouissi, Anita Raja, Thomas Koch, Alex Rybchuk, Axinia Radeva, Ashwath Rajan, Yiwen Huang, Hatim Diab, Ashish Tomar, Ronald J. Wapner. 55-72 [doi]
- Multi-task Prediction of Disease Onsets from Longitudinal Laboratory TestsNarges Razavian, Jake Marcus, David Sontag. 73-100 [doi]
- Deep Survival AnalysisRajesh Ranganath, Adler J. Perotte, Noémie Elhadad, David M. Blei. 101-114 [doi]
- Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic EpilepsyBilal Ahmed, Thomas Thesen, Karen E. Blackmon, Ruben Kuzniecky, Orrin Devinsky, Jennifer G. Dy, Carla E. Brodley. 115-133 [doi]
- gLOP: the global and Local Penalty for Capturing Predictive HeterogeneityRhiannon Rose, Daniel Lizotte. 134-149 [doi]
- Transferring Knowledge from Text to Predict Disease OnsetYun Liu, Collin M. Stultz, John V. Guttag, Kun-Ta Chuang, Fu-Wen Liang, Huey-Jen Su. 150-163 [doi]
- Preterm Birth Prediction: Stable Selection of Interpretable Rules from High Dimensional DataTruyen Tran 0001, Wei Luo, Dinh Q. Phung, Jonathan Morris, Kristen Rickard, Svetha Venkatesh. 164-177 [doi]
- Learning Robust Features using Deep Learning for Automatic Seizure DetectionPierre Thodoroff, Joelle Pineau, Andrew Lim. 178-190 [doi]
- Mitochondria-based Renal Cell Carcinoma Subtyping: Learning from Deep vs. Flat Feature RepresentationsPeter J. Schüffler, Judy Sarungbam, Hassan Muhammad, Ed Reznik, Satish K. Tickoo, Thomas J. Fuchs. 191-208 [doi]
- Clinical Tagging with Joint Probabilistic ModelsYoni Halpern, Steven Horng, David Sontag. 209-225 [doi]
- Diagnostic Prediction Using Discomfort Drawings with IBTMCheng Zhang, Hedvig Kjellström, Carl Henrik Ek, Bo C. Bertilson. 226-238 [doi]
- Uncovering Voice Misuse Using Symbolic MismatchMarzyeh Ghassemi, Zeeshan Syed, Daryush D. Mehta, Jarrad H. Van Stan, Robert E. Hillman, John V. Guttag. 239-252 [doi]
- Directly Modeling Missing Data in Sequences with RNNs: Improved Classification of Clinical Time SeriesZachary C. Lipton, David C. Kale, Randall C. Wetzel. 253-270 [doi]
- Deep Convolutional Neural Networks for Microscopy-Based Point of Care DiagnosticsJohn A. Quinn, Rose Nakasi, Pius K. B. Mugagga, Patrick Byanyima, William Lubega, Alfred Andama. 271-281 [doi]
- A Non-parametric Bayesian Approach for Estimating Treatment-Response Curves from Sparse Time SeriesYanbo Xu, Yanxun Xu, Suchi Saria. 282-300 [doi]
- Doctor AI: Predicting Clinical Events via Recurrent Neural NetworksEdward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun. 301-318 [doi]