We have accepted 97 short papers for poster presentation at the workshop.
These are listed below, with links to the paper on arXiv if provided by the authors.
These will appear at two possible poster sessions on Fri. Dec. 8 in Room 104A of Long Beach Convention Center:
Presenters: Remember to follow the posted poster instructions: Portrait format. Max size: 20 inches wide and 30 inches tall.
Poster Session 1 (10:20-10:50)
Correlational Dueling Bandits with Application to Clinical Treatment in Large Decision Spaces
Yanan Sui, Yisong Yue, Joel W. Burdick
Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networks
Amy Jin, Serena Yeung, Jeffrey Jopling, Jonathan Krause, Dan Azagury, Arnold Milstein, and Li Fei-Fei
Personalized Driver Stress Detection with Multi-task Neural Networks using Physiological Signals
Aaqib Saeed and Stojan Trajanovski
Real-valued (Medical) Time Series Generation with Recurrent Conditional GANs
Stephanie Hyland, Cristóbal Esteban and Gunnar Rätsch
Off-Policy Learning Under Noncompliance
Nathan Kallus.
Ask the doctor -- Improving drug sensitivity predictions through active expert knowledge elicitation
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski and Pekka Marttinen
Embedded Real-Time Fall Detection Using Deep Learning For Elderly Care
Hyunwoo Lee, Jooyoung Kim, Dojun Yang and Joon-Ho Kim
Automated Knee X-ray Report Generation
Aydan Gasimova, Giovanni Montana and Daniel Rueckert
Mondrian Processes for Flow Cytometry Analysis
Disi Ji, Eric Nalisnick, Padhraic Smyth
Cross-Modal Data Programming for Medical Images
Nishith Khandwala, Alexander Ratner, Jared Dunnmon, Roger Goldman, Matthew Lungren, Daniel Rubin and Chris Re
Physiological and behavioral profiling for nociceptive pain estimation using personalized multitask learning
Daniel Lopez-Martinez, Ognjen Rudovic and Rosalind Picard
CliNER 2.0: Accessible and Accurate Clinical Concept Extraction
Tristan Naumann, Willie Boag, Elena Sergeeva, Saurabh Kulshreshtha and Anna Rumshisky
A Public Benchmark for Clinical Prediction and Multitask Learning
Hrayr Harutyunyan, Hrant Khachatrian, David Kale, Greg Ver Steeg and Aram Galstyan
Spatial Anatomical Priors in Convolutional Networks for Unsupervised Biomedical Segmentation
Adrian Dalca, John Guttag and Mert Sabuncu
Anesthesiologist-level forecasting of hypoxemia with only SpO2 data using deep learning
Gabriel Erion, Hugh Chen, Scott M. Lundberg, Su-In Lee
Finding Algebraic Structure of Care in Time: A Deep Learning Approach
Phuoc Nguyen, Truyen Tran and Svetha Venkatesh
Co-training for Extraction of Adverse Drug Reaction Mentions from Tweets
Shashank Gupta, Manish Gupta, Vasudeva Varma, Sachin Pawar, Nitin Ramrakhiyani and Girish Keshav Palshikar
Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data
Petar Veličković, Laurynas Karazija, Nicholas D. Lane, Sourav Bhattacharya, Edgar Liberis, Pietro Liò, Angela Chieh, Otmane Bellahsen, and Matthieu Vegreville
Joint Concordance Index for Prognostic Models with Competing Risks
Kartik Ahuja and Mihaela van der Schaar.
Predicting Adolescent Suicide Attempts with Neural Networks
Harish S. Bhat, Sidra J. Goldman-Mellor
Deep Multi-Instance Learning for Concept Annotation from Medical Time Series Data
Sanjay Purushotham, Zhengping Che, Bo Jiang and Yan Liu
A Novel Data-Driven Framework for Risk Characterization and Prediction from Electronic Medical Records: A Case Study of Renal Failure
Prithwish Chakraborty, Vishrawas Gopalakrishnan, Sharon M.H. Alford, and Faisal Farooq
Deep Learning reduces 99.5% radiation risk for nuclear medicine functional imaging
Enhao Gong, Junshen Xu, John Pauly and Greg Zaharchuk
Generative Adversarial Networks for Electronic Health Records: A Framework for Exploring and Evaluating Methods for Predicting Drug-Induced Laboratory Test Trajectories
Alexandre Yahi, Rami Vanguri, Noémie Elhadad, Nicholas P. Tatonetti
Delineation of Skin Strata in Reflectance Confocal Microscopy Images using Recurrent Convolutional Networks with Toeplitz Attention
Alican Bozkurt, Kivanc Kose, Jaume Coll-Font, Christi Alessi-Fox, Dana H. Brooks, Jennifer G. Dy, Milind Rajadhyaksha
Distributed Stratified Locality Sensitive Hashing for Critical Event Prediction in the Cloud
Alessandro De Palma, Erik Hemberg, and Una-May O’Reilly
Survival-Supervised Topic Modeling with Anchor Words: Characterizing Pancreatitis Outcomes
George H. Chen, Jeremy C. Weiss
Towards Personalized Modeling of the Female Hormonal Cycle: Experiments with Mechanistic Models and Gaussian Processes
Iñigo Urteaga, David J. Albers, Marija Vlajic Wheeler, Anna Druet, Hans Raffauf and Noémie Elhadad
Personalized Gaussian Processes for Future Prediction of Alzheimer's Disease Progression
Kelly Peterson, Ognjen (Oggi) Rudovic, Ricardo Guerrero, and Rosalind W. Picard
Learning to Treat Sepsis with Multi-Output Gaussian Process Deep Recurrent Q-Networks
Joseph Futoma, Anthony Lin, Mark Sendak, Armando Bedoya, Meredith Clement, Cara O'Brien and Katherine Heller
Machine Learning-Based Risk Profile Classification: A Case Study for Heart Valve Surgery
Ulrich Bodenhofer, Bettina Haslinger-Eisterer, Alexander Minichmayer, Georg Hermanutz and Jens Meier
Evaluating deep variational autoencoders trained on pan-cancer gene expression
Gregory P. Way and Casey S. Greene
Image Segmentation to Distinguish Between Overlapping Human Chromosomes
R. Lily Hu, Jeremy Karnowski, Ross Fadely and Jean-Patrick Pommier
Adversarial Networks for Prostate Cancer Detection
Simon Kohl, David Bonekamp, Heinz-Peter Schlemmer, Kaneschka Yaqubi, Markus Hohenfellner, Boris Hadaschik, Jan-Philipp Radtke, Klaus Maier-Hein
A unifying Bayesian approach for preterm •brain-ageê prediction that models EEG sleep transitions over age
Kirubin Pillay and Maarten De Vos.
Deep Learning for Metagenomic Data: using 2D Embeddings and Convolutional Neural Networks
Thanh Hai Nguyen, Yann Chevaleyre, Edi Prifti, Nataliya Sokolovska and Jean-Daniel Zucker
Unsupervised Bayesian Inference for Fusing Sensory Estimates in Physiological Time-series Analysis
Tingting Zhu and David Clifton.
On the importance of normative data in speech-based assessment
Zeinab Noorian, Chloé Pou-Prom, Frank Rudzicz
A Hierarchical Generative Model of Electrocardiogram Records
Andrew Miller, Sendhil Mullainathan and Ziad Obermeyer
Multi-Task Learning for Extraction of Adverse Drug Reaction Mentions from Tweets
Shashank Gupta, Manish Gupta, Vasudeva Varma, Sachin Pawar, Nitin Ramrakhiyani and Girish Keshav Palshikar
Subject Selection on a Riemannian Manifold for Unsupervised Cross-subject Seizure Detection
Samaneh Nasiri Ghosheh Bolagh , Gari. D. Clifford
AWE-CM Vectors: Augmenting Word Embeddings with a Clinical Metathesaurus
Willie Boag and Mohamed Kane
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization
Adam McCarthy, Blanca Rodriguez and Ana Minchole
Viewpoint Invariant Convolutional Networks for Identifying Risky Hand Hygiene Scenarios
Michelle Guo, Albert Haque, Serena Yeung, Jeffrey Jopling, Lance Downing, Alexandre Alahi, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein and Li Fei-Fei
Causality Refined Diagnostic Prediction
Marcus Klasson, Kun Zhang, Bo C. Bertilson, Cheng Zhang, Hedvig Kjellström
Deep Risk: Timely Risk Scoring by a Recurrent Ensemble of Recurrent Neural Networks
Anton Nemchenko, William Zame and Mihaela Van Der Schaar
Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks
Jumana Dakka, Pouya Bashivan, Mina Gheiratmand
Poster Session 2 (15:20-15:50)
Personalized Survival Prediction with Contextual Explanation Networks
Maruan Al-Shedivat, Avinava Dubey and Eric Xing
Vision-Based Prediction of ICU Mobility Care Activities using Recurrent Neural Networks
Gabriel M. Bianconi, Rishab Mehra, Serena Yeung, Francesca Salipur, Jeffrey Jopling, Lance Downing, Albert Haque, Alexandre Alahi, Brandi Campbell, Kayla Deru, William Beninati, Arnold Milstein and Li Fei-Fei
Bayesian Nonparametric Clustering and Inference for Inpatient Health Care Utilization
Christoph Kurz and Laura Hatfield.
Deep Convolutional Networks for Detecting Arrhythmias from Pulsatile Signals
Ming-Zher Poh, Yukkee C. Poh, Chun-Ka Wong, Pak-Hei Chan and Chung-Wah Siu
Unsupervised Phenotype Scoring
Ioakeim Perros, Evangelos Papalexakis, Elizabeth Searles, Woosang Lim, Haesun Park and Jimeng Sun
Prediction-Constrained Topic Models for Antidepressant Recommendation
Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy, Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez
Counterfactual Reasoning with Dynamic Switching Models for HIV Therapy Selection
Sonali Parbhoo, Volker Roth and Finale Doshi-Velez
Internal Bleeding Detection by Multi-View Correlation Clustering of Central Venous Pressure
Eric Lei, Kyle Miller, Artur Dubrawski and Michael Pinsky
Data Augmentation for Aortic Valve Morphology Classification from Phase-Contrast MRI
Ke Xiao, Heliodoro Tejeda Lemus, Madalina Fiterau, Jason Fries, Christopher Ré, Euan Ashley and James Priest
Improving Matrix Completion in Healthcare through Missingness Estimation
Carolyn Kim, Erika Strandberg and Mohsen Bayati
Detection and Characterization of Illegal Marketing and Promotion of Prescription Drugs on Twitter
Janani Kalyanam and Tim Mackey.
A multiobjective deep learning approach for predictive classification in Neuroblastoma
Valerio Maggio, Marco Chierici, Giuseppe Jurman, Cesare Furlanello
Deep Reinforcement Learning for Sepsis Treatment
Aniruddh Raghu, Matthieu Komorowski, Imran Ahmed, Leo Celi, Peter Szolovits, Marzyeh Ghassemi
A deep learning-based method for relative location prediction in CT scan images
Jiajia Guo, Hongwei Du , Bensheng Qiu and Xiao Liang
Predicting Severe Sepsis Using Text from the Electronic Health Record
Phil Culliton, Michael Levinson, Alice Ehresman RN, Joshua Wherry, Jay S. Steingrub MD, Stephen I. Gallant
Unsupervised patient representations from clinical notes with interpretable classification decisions
Madhumita Sushil, Simon Šuster, Kim Luyckx, Walter Daelemans
Large Neural Network Based Detection of Apnea, Bradycardia and Desaturation Events
Antoine Honore, Saikat Chatterjee, Veronica Siljehav and Eric Herlenius
An Encoder-Decoder Model for ICD-10 Coding of Death Certificates
Elena Tutubalina and Zulfat Miftahutdinov
BioMM: Biologically-informed Multi-stage Machine learning for identification of epigenetic fingerprints
Junfang Chen and Emanuel Schwarz
Segmenting Brain Tumors with Symmetry
Hejia Zhang, Xia Zhu, and Theodore L. Willke
Riemannian tangent space mapping and elastic net regularization for cost-effective EEG markers of brain atrophy in Alzheimer's disease
Wolfgang Fruehwirt, Matthias Gerstgrasser, Pengfei Zhang, Leonard Weydemann, Markus Waser, Reinhold Schmidt, Thomas Benke, Peter Dal-Bianco, Gerhard Ransmayr, Dieter Grossegger, Heinrich Garn, Gareth W. Peters, Stephen Roberts, Georg Dorffner
Malaria Likelihood Prediction By Effectively Surveying Households Using Deep Reinforcement Learning
Pranav Rajpurkar, Vinaya Polamreddi and Anusha Balakrishnan
Predicting readmission risk from doctors' notes
Erin Craig, Carlos Arias, David Gillman
A global feature extraction model for the effective computer aided diagnosis of mild cognitive impairment using structural MRI images
Chen Fang, Panuwat Janwattanapong, Chunfei Li, and Malek Adjouadi
Synthetic Medical Images from Dual Generative Adversarial Networks
John Guibas, Tejpal Virdi, and Peter Li
The Impact of Missing Data in User-Generated mHealth Time Series
Li-Fang Cheng and Luca Foschini.
Interpreting Comorbidity Groups via Risk Trajectories in the Health Record
Bharat Srikishan, Rajesh Ranganath and Noemie Elhadad
Smartphone-based paroxysmal atrial fibrillation monitoring with robust generalization
Tamas Madl, David Madl
An Ensemble of Deep Convolutional Neural Networks for Alzheimer’s Disease Detection and Classification
Jyoti Islam and Yanqing Zhang
Detection-aided liver lesion segmentation using deep learning
MÍriam Bellver, Kevis-Kokitsi Maninis, Pont-Tuset Jordi, Xavier Gir„-I-Nieto, Jordi Torres and Luc Van Gool
Learning Deep Representations of Medical Images using Siamese CNNs with Application to Content-Based Image Retrieval
Yu-An Chung, and Wei-Hung Weng
Wrist Sensor Fusion Enables Robust Gait Quantification Across Walking Scenarios
Zeev Waks, Itzik Mazeh, Chen Admati, Michal Afek, Yonatan Dolan, and Avishai Wagner
Intelligent EHRs: Predicting Procedure Codes From Diagnosis Codes
Hasham Ul Haq, Rameel Ahmad, and Sibt Ul Hussain
Detection of Tooth caries in Bitewing Radiographs using Deep Learning
Muktabh Mayank Srivastava, Pratyush Kumar, Lalit Pradhan and Srikrishna Varadarajan
Highrisk Prediction from Electronic Medical Records via Deep Attention Networks
You Jin Kim, Yun-Geun Lee, Jeong Whun Kim, Jin Joo Park, Borim Ryu, and Jung-Woo Ha
Hybrid Gradient Boosting Trees and Neural Networks for Forecasting Operating Room Data
Hugh Chen, Scott Lundberg and Su-In Lee
Cost-Effective Active Learning for Melanoma Segmentation
Marc Gorriz, Axel Carlier, Emmanuel Faure and Xavier Giro-i-Nieto
Label scarcity in biomedicine: Data-rich latent factor discovery enhances phenotype prediction
Marc-Andre Schulz, Gael Varoquaux, Alexandre Gramfort, Bertrand Thirion and Danilo Bzdok
Modeling sepsis progression using hidden Markov models
Brenden Petersen, Michael Mayhew, Kalvin Ogbuefi, John Greene, Vincent Liu and Priyadip Ray
Bayesian Semi-nonnegative Tri-matrix Factorization to Identify Pathways Associated with Cancer Types
Sunho Park and Tae Hyun Hwang
Sum of previous inpatient serum creatinine measurements predicts acute kidney injury in rehospitalized patients
Samuel Weisenthal, Haofu Liao and Martin Zand
Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay
Hiba Chougrad, Hamid Zouaki, and Omar Alheyane
Modelling & Exploring Clinical Symptom Trajectories Post-Traumatic Brain Injury
Filip Dabek, Peter Hoover, Elizabeth Jimenez and Jesus Caban
Learning Physiological Decline via Random Structure Mortality Prediction Using Split RNNs
Matthew McDermott, Marzyeh Ghassemi, Nathan Hunt, Harini Suresh, Geeticka Chauhan, Tristan Naumann and Peter Szolovits
Towards Deep Learning Models for Psychological State Prediction using Smartphone Data: Challenges and Opportunities
Gatis Mikelsons, Matthew Smith, Abhinav Mehrotra, and Mirco Musolesi
Representation and Reinforcement Learning for Personalized Glycemic Control in Septic Patients
Wei-Hung Weng, Mingwu Gao, Ze He, Susu Yan and Peter Szolovits
Automated Training Set Generation for Aortic Valve Classification
Vincent Chen, Paroma Varma, Madalina Fiterau, Seung-Pyo Lee, James Priest and Christopher Ré