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ORCIDMLHC 2018: Palo Alto, CA, USA
- Finale Doshi-Velez, Jim Fackler, Ken Jung, David C. Kale, Rajesh Ranganath, Byron C. Wallace, Jenna Wiens:
Proceedings of the Machine Learning for Healthcare Conference, MLHC 2018, 17-18 August 2018, Palo Alto, California. Proceedings of Machine Learning Research 85, PMLR 2018 - Alexis Bellot, Mihaela van der Schaar:
Boosted Trees for Risk Prognosis. 2-16 - Bingbin Liu, Michelle Guo, Edward Chou, Rishab Mehra, Serena Yeung, N. Lance Downing, Francesca Salipur, Jeffrey Jopling, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein, Li Fei-Fei:
3D Point Cloud-Based Visual Prediction of ICU Mobility Care Activities. 17-29 - Stefan Hegselmann, Leonard Greulich, Julian Varghese, Martin Dugas:
Reproducible Survival Prediction with SEER Cancer Data. 49-66 - Audrey Durand, Charis Achilleos, Demetris Iacovides, Katerina Strati, Georgios D. Mitsis, Joelle Pineau:
Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis. 67-82 - Sebastian D. Goodfellow, Andrew J. Goodwin, Robert Greer, Peter C. Laussen, Mjaye Mazwi, Danny Eytan:
Towards Understanding ECG Rhythm Classification Using Convolutional Neural Networks and Attention Mappings. 83-101 - Yuan Luo, Chengsheng Mao, Yiben Yang, Fei Wang, Faraz S. Ahmad, Donna Arnett, Marguerite R. Irvin, Sanjiv J. Shah:
Integrating Hypertension Phenotype and Genotype with Hybrid Non-negative Matrix Factorization. 102-118 - Selin Merdan, Khurshid Ghani, Brian T. Denton:
Integrating Machine Learning and Optimization Methods for Imaging of Patients with Prostate Cancer. 119-136 - Bryan Lim, Mihaela van der Schaar:
Disease-Atlas: Navigating Disease Trajectories using Deep Learning. 137-160 - Gregory Yauney, Pratik Shah:
Reinforcement Learning with Action-Derived Rewards for Chemotherapy and Clinical Trial Dosing Regimen Selection. 161-226 - Murali Ravuri, Anitha Kannan, Geoffrey J. Tso, Xavier Amatriain:
Learning from the experts: From expert systems to machine-learned diagnosis models. 227-243 - Xenia Miscouridou, Adler J. Perotte, Noemie Elhadad, Rajesh Ranganath:
Deep Survival Analysis: Nonparametrics and Missingness. 244-256 - Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin:
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. 280-294 - Pascal Sturmfels, Saige Rutherford, Mike Angstadt, Mark Peterson, Chandra Sekhar Sripada, Jenna Wiens:
A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images. 295-311 - Matthew Engelhard, Hongteng Xu, Lawrence Carin, Jason A. Oliver, Matthew Hallyburton, F. Joseph McClernon:
Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model. 312-331 - Jeeheh Oh
, Jiaxuan Wang, Jenna Wiens:
Learning to Exploit Invariances in Clinical Time-Series Data using Sequence Transformer Networks. 332-347 - Vanessa D'Amario, Federico Tomasi, Veronica Tozzo, Gabriele Arnulfo, Annalisa Barla, Lino Nobili:
Multi-task multiple kernel learning reveals relevant frequency bands for critical areas localization in focal epilepsy. 348-382 - Devendra Singh Sachan, Pengtao Xie, Mrinmaya Sachan, Eric P. Xing:
Effective Use of Bidirectional Language Modeling for Transfer Learning in Biomedical Named Entity Recognition. 383-402 - Jen-Tang Lu, Stefano Pedemonte, Bernardo Bizzo, Sean Doyle, Katherine P. Andriole, Mark H. Michalski, R. Gilberto González, Stuart R. Pomerantz:
Deep Spine: Automated Lumbar Vertebral Segmentation, Disc-Level Designation, and Spinal Stenosis Grading using Deep Learning. 403-419 - Bryce Woodworth, Francesco Ferrari, Teofilo E. Zosa, Laurel D. Riek:
Preference Learning in Assistive Robotics: Observational Repeated Inverse Reinforcement Learning. 420-439 - Jingshu Liu, Zachariah Zhang, Narges Razavian:
Deep EHR: Chronic Disease Prediction Using Medical Notes. 440-464 - Disi Ji, Eric T. Nalisnick, Yu Qian, Richard H. Scheuermann, Padhraic Smyth:
Bayesian Trees for Automated Cytometry Data Analysis. 465-483 - Rafid Mahmood, Aaron Babier, Andrea McNiven, Adam Diamant, Timothy C. Y. Chan:
Automated Treatment Planning in Radiation Therapy using Generative Adversarial Networks. 484-499 - Jacob Fauber, Christian R. Shelton:
Modeling "Presentness" of Electronic Health Record Data to Improve Patient State Estimation. 500-513 - Scott Buffett, Catherine Pagiatakis, Di Jiang:
Pattern-Based Behavioural Analysis on Neurosurgical Simulation Data. 514-533 - Sana Tonekaboni, Mjaye Mazwi, Peter Laussen, Danny Eytan, Robert Greer, Sebastian D. Goodfellow, Andrew J. Goodwin, Michael Brudno, Anna Goldenberg:
Prediction of Cardiac Arrest from Physiological Signals in the Pediatric ICU. 534-550 - Jen J. Gong, John V. Guttag:
Learning to Summarize Electronic Health Records Using Cross-Modality Correspondences. 551-570 - Eric P. Lehman, Rahul G. Krishnan, Xiaopeng Zhao, Roger G. Mark, Li-Wei H. Lehman:
Representation Learning Approaches to Detect False Arrhythmia Alarms from ECG Dynamics. 571-586 - Willie Boag, Harini Suresh, Leo Anthony Celi, Peter Szolovits, Marzyeh Ghassemi:
Racial Disparities and Mistrust in End-of-Life Care. 587-602
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