We have accepted 81 short papers for poster presentation at the workshop. This year we have also established a new category and have selected 86 short papers for digital acceptances.

These are listed below, with links to the paper on arXiv if provided by the authors.

The poster acceptances will appear at two possible poster sessions on Sat. Dec. 8 in Palais des Congres de Montreal.

Digital acceptances will be featured on the website and during breaks at the workshop.

Presenters: Remember to follow the posted poster instructions: Portrait format. Max size: 24 inches wide and 32 inches tall. Digital acceptance slides can be submitted here.

Poster Session 1 (11:30-12:30)

Measuring the Severity of Depressive Symptoms from Spoken Language and 3D Facial Expressions

Albert Haque, Michelle Guo, Adam Miner and Li Fei-Fei

What is Interpretable? Using Machine Learning to Design Interpretable Decision-Support Systems

Owen Lahav, Nicholas Mastronarde and Mihaela van der Schaar

Natural language understanding for task oriented dialog in the biomedical domain in a low ressources context

Antoine Neuraz, Leonardo Campillos Llanos, Anita Burgun and Sophie Rosset

Clinical Concept Extraction with Contextual Word Embedding

Henghui Zhu, Ioannis Paschalidis and Amir Tahmasebi

MATCH-Net: Dynamic Prediction in Survival Analysis using Convolutional Neural Networks

Daniel Jarrett, Jinsung Yoon and Mihaela van der Schaar

Disease phenotyping using deep learning: A diabetes case study

Sina Rashidian, Janos Hajagos, Richard Moffitt, Fusheng Wang, Xinyu Dong, Kayley Abell-Hart, Kimberly Noel, Rajarsi Gupta, Mathew Tharakan, Veena Lingam, Joel Saltz and Mary Saltz

Glottal Closure Instants Detection From Pathological Acoustic Speech Signal Using Deep Learning

Gurunath Reddy M, Tanumay Mandal and K. Sreenivasa Rao

Model-Based Reinforcement Learning for Sepsis Treatment

Aniruddh Raghu, Matthieu Komorowski and Sumeetpal Singh

Predicting pregnancy using large-scale data from a women's health tracking mobile application

Bo Liu, Shuyang Shi, Yongshang Wu, Laura Symul, Emma Pierson and Jure Leskovec

PatchNet: Context-Restricted Architectures to Provide Visual Features for Image Classification

Adityanarayanan Radhakrishnan, Charles Durham, Ali Soylemezoglu and Caroline Uhler

Large-scale Generative Modeling to Improve Automated Veterinary Disease Coding

Yuhui Zhang, Allen Nie and James Zou

Estimating Causal Effects With Partial Covariates For Clinical Interpretability

Sonali Parbhoo, Mario Wieser and Volker Roth

Group induced graphical lasso allows for discovery of molecular pathways-pathways interactions

Veronica Tozzo, Federico Tomasi, Margherita Squillario and Annalisa Barla

A Framework for Implementing Machine Learning on Omics Data

Geoffroy Dubourg-Felonneau, Fergal Cotter, Timothy Cannings, Hannah Thompson, Nirmesh Patel, John W Cassidy, Belle Taylor and Harry W Clifford

Population-aware Hierarchical Bayesian Domain Adaptation

Vishwali Mhasawade, Nabeel Abdur Rehman and Rumi Chunara

An Analytics Approach to Randomized Controlled Trial Design for Hypertension Management

Anthony Bonifonte and Turgay Ayer

Modeling Irregularly Sampled Clinical Time Series

Satya Narayan Shukla and Benjamin Marlin

Deep Self-Organization: Interpretable Discrete Representation Learning on Medical Time Series

Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann and Gunnar Rätsch

Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs

Daniel Neil, Joss Briody, Alix Lacoste, Aaron Sim, Paidi Creed and Amir Saffariazar

Machine Learning for Survival Analysis: Empirical Risk Minimization for Censored Distribution-Free Regression with Applications

Guillaume Ausset, Stéphan Clémençon and François Portier

Semi-supervised Rare Disease Detection Using Generative Adversarial Network

Wenyuan Li, Yunlong Wang, Yong Cai, Corey Arnold, Emily Zhao and Yilian Yuan

Inferring Causality by Answering Naranjo Questionnaire using Electronic Health Records

Bhanu Pratap Singh Rawat, Fei Li and Hong Yu

Dynamic Measurement Scheduling for Adverse Event Forecasting using Deep RL

Chun-Hao Chang, Mingjie Mai and Anna Goldenberg

Privacy-Preserving Action Recognition for Smart Hospitals using Low-Resolution Depth Images

Edward Chou, Matthew Tan, Cherry Zou, Michelle Guo, Albert Haque, Arnold Milstein and Li Fei-Fei

Active Transfer Learning and Natural Language Processing For Deep Learning Liver Volumetry Using Surrogate Metrics

Brett Marinelli, Martin Kang, Michael Martini, John Zech, Joseph Titano, Samuel Cho, Anthony Costa and Eric Oermann

Registration of Sparse Clinical Images

Kathleen Lewis, Guha Balakrishnan, John Guttag and Adrian Dalca

Improving Clinical Predictions through Unsupervised Time Series Representation Learning

Xinrui Lyu, Matthias Hüser, Stephanie Hyland, George Zerveas and Gunnar Rätsch

Feature Selection Based on Unique Relevant Information for Health Data

Shiyu Liu and Mehul Motani

A Hybrid Instance-based Transfer Learning Method

Azin Asgarian, Parinaz Sobhani, Ji Chao Zhang, Madalin Mihailescu, Ahmed Bilal Ashraf and Babak Taati

Multiple Instance Learning for ECG Risk Stratification

Divya Shanmugam, Davis Blalock and John Guttag

Triage and Doctor Effort in Medical Machine Learning Prediction

Maithra Raghu, Jon Kleinberg and Sendhil Mullainathan

Measuring the Stability of EHR- and EKG-based Predictive Models

Andrew Miller

Inferring Multidimensional Rates of Aging from Cross-Sectional Data

Emma Pierson, Pang Wei Koh, Tatsunori Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson and Percy Liang

Learning from Few Subjects in the Presence of Large Amounts of Ambulatory Data

Jose Javier Gonzalez Ortiz, John Guttag, Robert E, Hillman, Daryush Mehta, Jarrad Van Stan and Marzyeh Ghassemi

Effective, Fast, and Memory-Efficient Compressed Multi-function Convolutional Neural Networks for More Accurate Medical Image Classification

Luna Zhang

Descriptive Analysis of ICU Patient Mobilization from Depth Videos

Laëtitia Shao, Zaid Nabulsi, Ruchir Rastogi, Bingbin Liu, Francesca Salipur, Serena Yeung, N, Lance Downing, William Beninati, Arnold Milstein and Li Fei-Fei

Learning Global Additive Explanations for Neural Nets Using Model Distillation

Sarah Tan, Rich Caruana, Giles Hooker, Paul Koch and Albert Gordo

Towards generative adversarial networks as a new paradigm for radiology education

Samuel Finlayson, Hyunkwang Lee, Isaac Kohane and Luke Oakden-Rayner

Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images

Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Pavitra Krishnaswamy and Jayashree Kalpathy-Cramer

Generative models for clinical imaging genetic analysis

Francesco Paolo Casale, Nicolo Fusi, Jennifer Listgarten and Adrian Dalca

Poster Session 2 (13:30-14:30)

Automatic Documentation of ICD Codes with Far-Field Speech Recognition

Albert Haque and Corinna Fukushima

Distinguishing correlation from causation using genome-wide association studies

Luke O'Connor and Alkes Price

Prototypical Clustering Networks for Dermatological Disease Diagnosis

Viraj Uday Prabhu and Anitha Kannan

Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network

Nathaniel Braman, David Beymer and Ehsan Dehghan

Cluster-Based Learning from Weakly Labeled Bags in Digital Pathology

Shazia Akbar and Anne Martel

Decorrelating the Brain Dynamics with Recurrent Neural Network for Schizophrenia Classification

Byung-Hoon Kim and Jong Chul Ye

Estimation of Individual Treatment Effect in Latent Confounder Models via Adversarial Learning

Changhee Lee, Nicholas Mastronarde and Mihaela van der Schaar

Generative Modeling and Inverse Imaging of CardiacTransmembrane Potential

Sandesh Ghimire, Jwala Dhamala, Prashnna Kumar Gyawali and Linwei Wang

Unsupervised learning with contrastive latent variable models

Kristen Severson, Soumya Ghosh and Kenney Ng

Radiotherapy Target Contouring with Convolutional Gated Graph Neural Network

Chun-Hung Chao, Yen-Chi Cheng, Hsien-Tzu Cheng, Chi-Wen Huang, Tsung-Ying Ho, Chen-Kan Tseng, Le Lu and Min Sun

DeepSPINE: automated lumbar spinal stenosis grading using deep learning

Jen-Tang Lu, Stefano Pedemonte, Bernardo Bizzo, Sean Doyle, Katherine Andriole, Mark Michalski, R, Gilberto Gonzalez and Stuart Pomerantz

Compensated Integrated Gradients to Reliably Interpret EEG Classification

Kazuki Tachikawa, Yuji Kawai, Jihoon Park and Minoru Asada

Childhood obesity prediction and risk factor analysis from nationwide health records

Hagai Rossman, Smadar Shilo, Nitzan Artzi and Eran Segal

TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes

Monica Agrawal, Griffin Adams, Nathan Nussbaum and Benjamin Birnbaum

Isolating Cost Drivers in Interstitial Lung Disease Treatment Using Nonparametric Bayesian Methods

Seth Stafford and Christoph Kurz

Deep Ensemble Tensor Factorization for Longitudinal Patient Trajectories Classification

Edward De Brouwer, Jaak Simm, Adam Arany and Yves Moreau

Automatic Diagnosis of Short-Duration 12-Lead ECG using Deep Convolutional Network

Antonio H, Ribeiro, Manoel Horta Ribeiro, Gabriela Paixão, Derick Oliveira, Paulo R, Gomes, Jéssica A, Canazart, Milton Pifano, Wagner Meira Jr, Thomas B, Schön and Antonio Luiz Ribeiro

A Bayesian model of acquisition and clearance of bacterial colonization

Marko Järvenpää, Mohamad Sater, Georgia Lagoudas, Paul Blainey, Loren Miller, James McKinnell, Susan Huang, Yonatan Grad and Pekka Marttinen

A Probabilistic Model of Cardiac Physiology and Electrocardiograms

Andrew Miller, Sendhil Mullainathan, Ziad Obermeyer, John Cunningham and David Blei

Curriculum Learning for Training Neural Networks on Medical Data

Rasheed El-Bouri, David Clifton and Tingting Zhu

Automated Radiation Therapy Treatment Planning using 3-D Generative Adversarial Networks

Aaron Babier, Rafid Mahmood, Andrea McNiven, Adam Diamant and Timothy Chan

Imputation of Clinical Covariates in Time Series

Dimitris Bertsimas, Agni Orfanoudaki and Colin Pawlowski

Advancing PICO Element Detection in Medical Text via Deep Neural Networks

Di Jin and Peter Szolovits

Time Aggregation and Model Interpretation for Deep Multivariate Longitudinal Patient Outcome Forecasting Systems in Chronic Ambulatory Care

Beau Norgeot, Dmytro Lituiev, Benjamin Glicksberg and Atul Butte

Deep Discriminative Fine-Tuning for Cancer Type Classification

Alena Harley

ProstateGAN: Mitigating Data Bias via Prostate Diffusion Imaging Synthesis with Generative Adversarial Networks

Xiaodan Hu, Audrey G, Chung, Paul Fieguth and Alexander Wong

Predicting Language Recovery after Stroke with Convolutional Networks on Stitched MRI

Yusuf Roohani, Noor Sajid, Pranava Madhyastha, Thomas Hope and Cathy Price

The Effect of Heterogeneous Data for Alzheimer's Disease Detection from Speech

Aparna Balagopalan, Jekaterina Novikova, Frank Rudzicz and Marzyeh Ghassemi

Corresponding Projections for Orphan Screening

Sven Giesselbach, Katrin Ullrich, Michael Kamp, Daniel Paurat and Thomas Gärtner

Deep Learning with Attention to Predict Gestational Age of the Fetal Brain

Liyue Shen, Edward Lee, Katie Shpanskaya and Kristen Yeom

Leveraging Routine Pre-Operative Blood Draws to Predict Hemorrhagic Shock During Surgery

Xinyu Li, Michael R, Pinsky, Gilles Clermont and Artur Dubrawski

Rank Projection Trees for Multilevel Neural Network Interpretation

Jonathan Warrell, Hussein Mohsen and Mark Gerstein

Using permutations to assess confounding in machine learning applications for digital health

Elias Chaibub Neto, Abhishek Pratap, Thanneer Perumal, Meghasyam Tummalacherla, Brian Bot, Lara Mangravite and Larsson Omberg

Robustness against the channel effect in pathological voice detection

Yi-Te Hsu, Zining Zhu, Chi-Te Wang, Shih-Hau Fang, Frank Rudzicz and Yu Tsao

Learning to Unlearn: Building Immunity to Dataset Bias in Medical Imaging Studies

Ahmed Ashraf, Shehroz Khan, Nikhil Bhagwat, Mallar Chakravarty and Babak Taati

Modeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders

Denny Wu, Hirofumi Kobayashi, Charles Ding, Cheng Lei, Keisuke Goda and Marzyeh Ghassemi

Unsupervised Multimodal Representation Learning across Medical Images and Reports

Tzu-Ming Harry Hsu, Wei-Hung Weng, Willie Boag, Matthew McDermott and Peter Szolovits

Deep Sequence Modeling for Hemorrhage Diagnosis

Fabian Falck, Michael Pinsky and Artur Dubrawski

Unsupervised Medical Image Imputation via Variational Inference of Deep Subspaces

Adrian Dalca, John Guttag and Mert Sabuncu

Unsupervised Deep Neural Networks Harmonize Multiple Data Sources and Explain Inherent Biases

Nelson Johansen and Gerald Quon

Unsupervised Pseudo-Labeling for Extractive Summarization on Electronic Health Records

Xiangan Liu, Keyang Xu, Pengtao Xie and Eric Xing

Digital Acceptances

Robust Active Learning for Electrocardiographic Signal Classification

Xu Chen and Saratendu Sethi

Identification of Predictive Subpopulations in Heterogeneous Samples

Bryan He, James Zou and Matt Thomson

Can We Estimate the Health-Related Quality of Life of Twitter Users Using Tweets? A Feasibility Study

Karthik Sarma, Brennan M, R, Spiegel, Mark W, Reid, Shawn Chen, Raina M, Merchant, Emily Seltzer and Corey W, Arnold

Class Augmented Semi-Supervised Learning for Practical Clinical Analytics on Physiological Signals

Arijit Ukil, Soma Bandyopadhyay, Chetanya Puri and Arpan Pal

Cross-domain Transfer Learning for Cardiovascular Diseases

Girmaw Abebe Tadesse, Tingting Zhu and David Clifton

Reliable uncertainty estimate for antibiotic resistance classification with Stochastic Gradient Langevin Dynamics

Md-Nafiz Hamid and Iddo Friedberg

Adjusting for Confounding in Unsupervised Latent Representations of Images

Craig A Glastonbury, Michael Ferlaino, Christoffer Nellaker and Cecilia Lindgren

Generative Adversarial Frameworkfor Learning Multiple Clinical Tasks

Mina Rezaei, Haojin Yang and Christoph Meinel

Learning Optimal Personalized Treatment Rules Using Robust Regression Informed K-NN

Ruidi Chen and Ioannis Paschalidis

Unsupervised learning with GLRM feature selection reveals novel traumatic brain injury phenotypes

Aaron Masino and Kaitlin Folweiler

An adaptive treatment recommendation and outcome prediction model for metastatic melanoma

Xue Teng, Fuad Gwadry, Haley McConkey, Scott Ernst and Femida Gwadry-Sridhar

Feature Selection for Survival Analysis with Competing Risks using Deep Learning

Carl Rietschel, Jinsung Yoon and Mihaela van der Schaar

Application of Clinical Concept Embeddings for Heart Failure Prediction in UK EHR data

Spiros Denaxas, Pontus Stenetorp, Sebastian Riedel, Maria Pikoula, Richard Dobson and Harry Hemingway

Sreenivasa Rao

Gurunath Reddy M, Tanumay Mandal and K

Machine Learning on Electronic Health Records: Models and Features Usages to predict Medication Non-Adherence

Thomas Janssoone, Pierre Rinder, Pierre Hornus, Clémence Bic and Dora Kanoun

Digital Breast Tomosynthesis Reconstruction using Deep Learning

Nikita Moriakov, Koen Michielsen, Jonas Adler, Ritse Mann, Ioannis Sechopoulos and Jonas Teuwen

A Deep Latent-Variable Model application to Select Treatment Intensity in Survival Analysis

Cedric Beaulac, Jeffrey S, Rosenthal and David Hodgson

FADL:Federated-Autonomous Deep Learning for Distributed Electronic Health Record

Dianbo Liu, Tim Miller, Raheel Sayeed and Kenneth Mandl

Early Stratification of Patients at Risk for Postoperative Complications after Elective Colectomy

Wen Wang, Rema Padman and Nirav Shah

Explainable Genetic Inheritance Pattern Prediction

Edmond Cunningham, Dana Schlegel and Andrew DeOrio

In-silico Risk Analysis of Personalized Artificial Pancreas Controllers via Rare-event Simulation

Matthew O'Kelly, Aman Sinha, Justin Norden and Hongseok Namkoong

Sub-linear Privacy-preserving Search with Unsecured Server and Semi-honest Parties

Beidi Chen

EEG Seizure Detection via Deep Neural Networks: Application and Interpretation

Jiening Zhan, Hector Yee, Ian Covert, Jiang Wu, Albee Ling, Matthew Shore, Eric Teasley, Rebecca Davies, Tiffany Kung, Justin Tansuwan, John Hixson and Ming Jack Po

General-to-Detailed GAN for Infrequent Class Medical Images

Tatsuki Koga, Naoki Nonaka, Jun Sakuma and Jun Seita

Stochastic Optimal Control of Epidemic Processes in Networks

Lars Lorch, Abir De, Samir Bhatt, William Trouleau, Utkarsh Upadhyay and Manuel Gomez Rodriguez

Multivariate Time-series Similarity Assessment via Unsupervised Representation Learning and Stratified Locality Sensitive Hashing: Application to Early Acute Hypotensive Episode Detection

Jwala Dhamala, Emmanuel Azuh, Abdullah Al-Dujaili, Jonathan Rubin and Una-May O'Reilly

Predicting Diabetes Disease Evolution Using Financial Records and Recurrent Neural Networks

Rafael Sousa, Anderson Soares and Lucas Pereira

A Distillation Approach to Data Efficient Individual Treatment Effect Estimation

Maggie Makar, Adith Swaminathan and Emre Kiciman

Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays

Sejin Park, Woochan Hwang and Kyu-Hwan Jung

Vision-Based Gait Analysis for Senior Care

Evan Darke, Anin Sayana, Kelly Shen, David Xue, Jun-Ting Hsieh, Zelun Luo, Li-Jia Li, N, Lance Downing, Arnold Milstein and Li Fei-Fei

Alternating Loss Correction for Preterm-Birth Prediction from EHR Data with Noisy Labels

Sabri Boughorbel, Fethi Jarray, Neethu Venugopal and Haithum Elhadi

Multimodal Medical Image Retrieval based on Latent Topic Modeling

Mandikal Vikram, Aditya Anantharaman, Suhas B S and Sowmya Kamath S

Knowledge-driven generative subspaces for modeling multi-view dependencies in medical data

Parvathy Sudhir Pillai and Tze Yun Leong

Towards Continuous Domain adaptation for Healthcare

Rahul V, Hariharan Ravishankar and Saihareesh Anamandra

Structure-Based Networks for Drug Validation

Cătălina Cangea, Arturas Grauslys, Francesco Falciani and Pietro Liò

Personalizing Intervention Probabilities By Pooling

Sabina Tomkins, Susan Murphy and Predrag Klasnja

Computational EEG in Personalized Medicine: A study in Parkinson’s Disease

Sebastian Keller, Maxim Samarin and Volker Roth

Semi-unsupervised Learning of Human Activity using Deep Generative Models

Matthew Willetts, Aiden Doherty, Chris Holmes and Stephen Roberts

Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection

Luke Harries, Suyi Zhang, John Shawe-Taylor, Jonathan Sinai, Nirmesh Patel, John W Cassidy, Belle Taylor and Harry W Clifford

HYPE: A High Performing NLP System for Automatically Detecting Hypoglycemia Events from Electronic Health Record Notes

Yonghao Jin, Fei Li and Hong Yu

Structured RNNs and spatio-temporal graphs for motion analysis in echocardiography videos

Arijit Patra

Interpretable Clustering via Optimal Trees

Dimitris Bertsimas, Agni Orfanoudaki and Holly Wiberg

Modeling Treatment Delays for Patients Using Feature Label Pairs in a Time Series

Weiyu Huang, Yunlong Wang, Li Zhou, Emily Zhao, Yilian Yuan and Alejandro Ribero

Real-Time Sleep Staging using Deep Learning on a Smartphone for a Wearable EEG

Abhay Koushik, Judith Amores Fernandez and Pattie Maes

Medical Concept Normalization in Social Media Posts with Recurrent Neural Networks

Elena Tutubalina and Zulfat Miftakhutdinov

Patient Subtyping with Disease Progression and Irregular Observation Trajectories

Nikhil Galagali and Minnan Xu-Wilson

Bayesian deep neural networks for low-cost neurophysiological markers of Alzheimer’s disease severity

Wolfgang Fruehwirt, Adam Cobb, Stephen Roberts and Georg Dorffner

Integrating omics and MRI data with kernel-based tests and CNNs to identify rare genetic markers for Alzheimer's disease

Stefan Konigorski, Shahryar Khorasani and Christoph Lippert

Task incremental learning of Chest X-ray data on compact architectures

Arijit Patra

Semantically-aware population health risk analyses

Alexander New, Sabbir Rashid, John Erickson, Deborah McGuinness and Kristin Bennett

Hierarchical Deep Learning Classification of Unstructured Pathology Reports to Automate ICD-O Morphology Grading

Waheeda Saib and Tapiwa Chiwewe

Examining the measurement of quality in healthcare using artificial intelligence methods: a study of quality in long-term care

Pouria Mashouri, Andrea Iaboni and Babak Taati

Modeling disease progression in longitudinal EMR data using continuous-time hidden Markov models

Aman Verma, Guido Powell, Yu Luo, David Stephens and David Buckeridge

Unsupervised Phenotype Identification from Clinical Notes for Association Studies in Cancer

Stefan Stark, Stephanie L Hyland, Julia Vogt and Gunnar Rätsch

Probabilistic modelling of gait for remote passive monitoring applications

Yordan Raykov, Luc Evers, Reham Badawy, Marjan Faber, Bastiaan Bloem and Max Little

Confounding-Robust Policy Improvement

Nathan Kallus and Angela Zhou

Partial Least Squares Regression in Alzheimer's disease: finding latent shared structures between biomarkers and imaging features

Adrià Casamitjana and Veronica Vilaplana

Advance Prediction of Ventricular Tachyarrhythmias using Patient Metadata and Multi-Task Networks

Marek Rei, Josh Oppenheimer and Marek Sirendi

Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning

Mengqi Jin

Boosting pathology detection in infants by deep transfer learning from adult speech

Charles Onu, Gautam Bhattacharya and Doina Precup

Predicting Electroencephalogram Impressions using Deep Neural Networks

Siddharth Biswal, Michael Brandon Westover and Jimeng Sun

Prediction of New Onset Diabetes after Liver Transplant

Angeline Yasodhara, Mamatha Bhat and Anna Goldenberg

Direct Uncertainty Prediction for Medical Second Opinions

Maithra Raghu, Katy Blumer, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan and Jon Kleinberg

Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation

Bret Nestor, Matthew McDermott, Geeticka Chauhan, Tristan Naumann, Michael Hughes, Anna Goldenberg and Marzyeh Ghassemi

Web Applicable Computer-aided Diagnosis of Glaucoma Using Deep Learning

Mijung Kim, Ho-Min Park, Jasper Zuallaert, Olivier Janssens, Sofie Van Hoecke and Wesley De Neve

A New NMT Model for Translating Clinical Texts from English to Spanish

Rumeng Li, Xun Wang and Hong Yu

Cross-Modal Medical Embedding Alignment Without Human Annotations

James Mullenbach, Ioakeim Perros, Xiaoqian Jiang and Jimeng Sun

Dual Objective Approach Using A Convolutional Neural Network for Magnetic Resonance Elastography

Ligin Solamen, Yipeng Shi and Justice Amoh

A Sequence of Two Studies to Learn & Test Heterogeneous Treatment Sub-groups: Effects of Cost Exposure on Use of Outpatient Care

Rahul Ladhania, Amelia Haviland, Neeraj Sood and Ateev Mehrotra

Discovering heterogeneous subpopulations for fine-grained analysis of opioid use and opioid use disorders

Jen Gong, Abigail Jacobs, Toby Stuart and Mathijs de Vaan

Privacy-Preserving Distributed Deep Learning for Clinical Data

Brett Beaulieu-Jones, Steven Wu, William Yuan, Samuel Finlayson and Isaac Kohane

A Comparison of Methods for Progression Endotype Detection in Amyotrophic Lateral Sclerosis

Hamish Tomlinson, Romain Studer, Poojitha Ojamies, Joanna Holbrook and Paidi Creed

Practical Window Setting Optimization for Medical Image Deep Learning

Hyunkwang Lee, Myeongchan Kim and Synho Do

Predicting progressions and clinical subtypes of Alzheimer’s disease using machine learning

Vipul Satone, Rachneet Kaur, Faraz Faghri and Roy Campbell

Using Multitask Learning to Improve 12-Lead Electrocardiogram Classification

John Hughes, Taylor Sittler, Anthony Joseph, Jeffrey Olgin, Joseph Gonzalez and Geoffrey Tison

METCC: METric learning for Confounder Control Making distance matter in high dimensional biological analysis

Kabir Manghnani, Adam Drake, Nathan Wan and Imran Haque

Atlas Construction and Improved Registration of Medical Images with CNN Frameworks

Adrian Dalca, Guha Balakrishnan, John Guttag and Mert Sabuncu

Uncertainty-Aware LSTM with Attention Early Warning System

Farah Shamout, Tingting Zhu, Peter Watkinson and David Clifton

Deep Learning approach for predicting 30 day readmissions after Coronary Artery Bypass Graft Surgery

Ramesh Manyam, Yanqing Zhang, William Keeling, Jose Binongo, Michael Kayatta and Seth Carter

Leveraging Deep Stein's based Risk Estimator for Unsupervised X-ray Denoising

Fahad Shamshad, Awais Muhammad, Muhammad Asim, Zain Lodhi and Muhammad Umair

Phenotype inference with Semi-Supervised Mixed Membership Models

Victor Rodriguez and Adler Perotte

Predicting Blood Pressure Response to Fluid Bolus Therapy Using Attention-Based Neural Networks

Uma M, Girkar, Ryo Uchimido, Li-Wei H, Lehman, Peter Szolovits, Leo A Celi and Wei-Hung Weng,

Generalizability of predictive models for intensive care unit patients

Alistair Johnson, Tom Pollard and Tristan Naumann

Towards Robust Lung Segmentation in Chest Radiographs with Deep Learning

Jyoti Islam and Yanqing Zhang

Relation Networks for Optic Disc and Fovea Localization in Retinal Images

Sudharshan Chandra Babu, Shishira R Maiya and Sivasankar Elango

Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data

Haraldur Hallgrimsson, Filip Jankovic, Tim Althoff and Luca Foschini