We have accepted 97 extended abstracts for presentation at the workshop.
These are listed below, with links to the paper on arXiv if provided by the authors.
The poster acceptances will appear on Friday Dec. 13 in Vancouver.
Differentially Private Survival Function Estimation
Lovedeep Gondara, Ke Wang
Migration through Machine Learning Lens - Predicting Sexual and Reproductive Health Vulnerability of Young Migrants
Amber Nigam, Pragati Jaiswal, Uma Girkar, Teertha Arora, Leo A Celi
Individualized Feature Importance for Time Series Risk Prediction Models
Sana Tonekaboni; Shalmali Joshi; Anna Goldenberg
Multimodal Multitask Representation Learning for Pathology Biobank Metadata Prediction
Wei-Hung Weng, Yuannan Cai, Angela Lin, Fraser Tan, Po-Hsuan Cameron Chen
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
Haoran Zhang*, Amy X. Lu*, Mohamed Abdalla, Matthew McDermott, Marzyeh Ghassemi
Global Saliency: Aggregating Saliency Maps to Assess Dataset Artefact Bias
Jacob Pfau, Albert T. Young, Maria L. Wei, Michael J. Keiser
Learning the Graphical Structure of Electronic Health Records with\\Graph Convolutional Transformer for Predictive Healthcare
Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Emily Xue, Andrew M. Dai
Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
Hyeon-Woo Lee, Mert R. Sabuncu, Adrian V. Dalca
Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation
Hyeon-Woo Lee, Mert R. Sabuncu, Adrian V. Dalca
Deep Learning Mobile Application Towards Malaria Diagnosis
Martha Shaka*, Nyamos Waigama, Emilian Ngatunga, Halidi Maneno, Said Said, Said Mmaka, Frederick Apina,Simon Chaula, Emani Sulutya and Merikiadi Mashaka
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving
Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu
A Bayesian Approach to Modelling Longitudinal Data in Electronic Health Records
Alexis Bellot, Mihaela van der Schaar
Cellular State Transformations using Generative Adversarial Networks
Colin Targonski, Benjamin T. Shealy, Melissa C. Smith, F. Alex Feltus
Errors-in-variables Modeling of Personalized Treatment-Response Trajectories
Guangyi Zhang, Reza A. Ashrafi, Anne Juuti, Kirsi Pietiläinen, Pekka Marttinen
Phenotyping of Clinical Notes with Improved Document Classification Models Using Contextualized Neural Language Models
Andriy Mulyar, Elliot Schumacher, Masoud Rouhizadeh, Mark Dredze
A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation
Irene Li, Michihiro Yasunaga, Muhammed Yavuz Nuzumlalı, Cesar Caraballo, Shiwani Mahajan, Harlan Krumholz and Dragomir Radev
Synthetic Epileptic Brain Activities using GANs
Damian Pascual, Amir Aminifar, David Atienza, Philippe Ryvlin, Roger Wattenhofer
Human-centric Metric for Accelerating Pathology Reports Annotation
Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li, Wei-Hung Weng, Angela Lin, Krishna Gadepalli, Yuannan Cai
Explainable Prediction of Adverse Outcomes Using Clinical Notes
Justin R. Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi
Federated Uncertainty-Aware Learning for Distributed Hospital EHR Data
Sabri Boughorbel, Fethi Jarray, Neethu Venugopal, Shabir Moosa, Haithum Elhadi, Michel Makhlouf
Modeling glaucoma progression in a population from spatiotemporal measurements
Supriya Nagesh, Alexander Moreno, Hiroshi Ishikawa, Gadi Wollstein, Joel S. Schuman, James M. Rehg
Generation of heterogeneous EHRs using GANs
Kieran Chin-Cheong, Thomas Sutter, Julia E. Vogt
Deep Survival Experts: A Fully Parametric Survival Regression Model
Xinyu Li*, Chirag Nagpal*, Artur Dubrawski
Classification as Decoder: Trading Flexibility for Control in Medical Dialogue
Sam Shleifer, Manish Chablani, Namit Katariya, Anitha Kannan, Xavier Amatriain
Are Deep Learning Chest X-ray Classifiers Fair?
Laleh Seyyed-Kalantari, Guanxiong Liu, Matthew McDermott, Marzyeh Ghassemi
Advancing PICO Element Detection in Biomedical Text via Deep Neural Networks
Di Jin, Peter Szolovits
Transfer Learning in 4D for Breast Cancer Diagnosis using Dynamic Contrast-Enhanced Magnetic Resonance Imaging
Qiyuan Hu, Heather M. Whitney, Maryellen L. Giger
Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making
Devin Taylor, Simeon Spasov, Pietro Lio
Time-Series Analysis via Low-Rank Matrix Factorization Applied to Infant-Sleep Data
Sheng Liu, Mark Cheng, Hayley Brooks, Wayne Mackey, David J. Heeger, Esteban G. Tabak, Carlos Fernandez-Granda
Towards the Use of Neural Networks for Influenza Prediction at Multiple Spatial Resolutions
Emily L. Aiken, Andre T. Nguyen, Mauricio Santillana
Combining human cell line transcriptome analysis and Bayesian inference to build trustworthy machine learning models for prediction of animal toxicity in drug development
Laura-Jayne Gardiner, Anna Paola Carrieri, Jenny Wilshaw, Stephen Checkley, Edward O Pyzer-Knapp, Ritesh Krishna
Discovering Invariances in Healthcare Neural Networks
Mohammad Taha Bahadori, Layne C. Price
Migration through Machine Learning Lens - Predicting Sexual and Reproductive Health Vulnerability of Young Migrants
Amber Nigam, Pragati Jaiswal, Uma Girkar, Teertha Arora, Leo A. Celi
Generating an Explainable ECG Beat Space With Variational Auto-Encoders
Tom Van Steenkiste, Dirk Deschrijver, Tom Dhaene
Estimating counterfactual treatment outcomes over time through adversarially balanced representations
Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders
Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar
Globally-aware multiple instance classifier for breast cancer screening
Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Kyunghyun Cho, Gene Kim, Linda Moy, Krzysztof J. Geras
Globally-aware multiple instance classifier for breast cancer screening
Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras
Modeling patterns of smartphone usage and their relationship to cognitive health
Jonas Rauber, Emily B. Fox, Leon A. Gatys
SAVEHR: Self Attention Vector Representations for EHR based Personalized Chronic Disease Onset Prediction and Interpretability
Sunil Mallya, Marc Overhage, Sravan Bodapati, Navneet Srivastava, Sahika Genc
Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning
Chufan Gao, Fabian Falck, Mononito Goswami, Anthony Wertz, Michael R. Pinsky, Artur Dubrawski
Learning the Graphical Structure of Electronic Health Records with Graph Convolutional Transformer
Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Emily Xue, Andrew M. Dai
Differential Privacy-enabled Federated Learning for Sensitive Health Data
Olivia Choudhury, Aris Gkoulalas-Divanis, Theodoros Salonidis, Issa Sylla, Yoonyoung Park, Grace Hsu, Amar Das
Learning from Data-Rich Problems: A Case Study on Genetic Variant Calling
Ren Yi, Pi-Chuan Chang, Gunjan Baid, Andrew Carroll
Causality-based tests to detect the influence of confounders on mobile health diagnostic applications: a comparison with restricted permutations
Elias Chaibub Neto, Meghasyam Tummalacherla, Lara Mangravite, Larsson Omberg
ZiMM: a deep learning model for long term adverse events with non-clinical claims data
Emmanuel Bacry, Stéphane Gaïffas, Anastasiia Kabeshova, Yiyang Yu
Extracting evidence of supplement-drug interactions from literature
Lucy L. Wang, Oyvind Tafjord, Sarthak Jain, Arman Cohan, Sam Skjonsberg, Carissa Schoenick, Nick Botner, Waleed Ammar
Global Saliency: Aggregating Saliency Maps to Assess Dataset Artefact Bias
Jacob Pfau, Albert T. Young, Maria L. Wei, Michael J. Keiser
Harmonic Mean Point Processes: Proportional Rate Error Minimization for Obtundation Prediction
Yoonjung Kim, Jeremy C. Weiss
Evaluating robustness of language models for chief complaint extraction from patient-generated text
Ilya Valmianski, Caleb Goodwin, Ian M. Finn, Naqi Khan, Daniel S. Zisook
Modelling EHR timeseries by restricting feature interaction
Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai
Domain-Relevant Embeddings for Medical Question Similarity
Clara McCreery, Namit Katariya, Anitha Kannan, Manish Chablani, Xavier Amatriain
Improved Hierarchical Patient Classification with Language Model Pretraining over Clinical Notes
Jonas Kemp, Alvin Rajkomar, Andrew M. Dai
Intelligent Pooling with Dynamic Populations: Thompson Sampling for Mobile Health
Sabina Tomkins, Peng Liao, Predrag Klasnja, Serena Yeung, Susan Murphy
Long-range Prediction of Vital Signs Using Generative Boosting via LSTM Networks
Shiyu Liu and Mehul Motani
Detecting cutaneous basal cell carcinomas in ultra-high resolution and weakly labelled histopathological images
Susanne Kimeswenger, Elisabeth Rumetshofer, Markus Hofmarcher, Philipp Tschandl, Harald Kittler, Sepp Hochreiter, Wolfram Hötzenecker, Günter Klambauer
Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging
Luke Oakden-Rayner*, Jared Dunnmon*, Gustavo Carneiro, Christopher Ré
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving
Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu
Embryo Staging with Weakly-Supervised Region Selection and Dynamically-Decoded Predictions
Tingfung Lau, Nathan Ng, Julian Gingold, Nina Desai, Julian McAuley, Zachary C. Lipton
Open Set Diagnosis
Viraj Prabhu, Anitha Kannan, Geoffrey J. Tso, Namit Katariya, Manish Chablani, David Sontag, Xavier Amatriain
Temporal PSOM - An Interpretable Clustering Method for Tracking Health States in the ICU
Laura Manduchi, Matthias Hüser, Gunnar Rätsch, Vincent Fortuin
Deep Generalized Method of Moments for Instrumental Variable Analysis
Andrew Bennett, Nathan Kallus, Tobias Schnabel
Assigning Medical Codes at the Encounter Level by Paying Attention to Documents
Han-Chin Shing, Guoli Wang, Philip Resnik
Federated and Differentially Private Learning for Electronic Health Records
Stephen R. Pfohl, Andrew M. Dai, Katherine Heller
The medical deconfounder: assessing treatment effects with electronic health records
Linying Zhang, Yixin Wang, Anna Ostropolets, Jami J. Mulgrave, David M. Blei, George Hripcsak
Text2Node: a Cross-Domain System for Mapping Arbitrary Phrases to a Taxonomy
Rohollah Soltani, Alexandre Tomberg
Prediction Focused Topic Models for Electronic Health Records
Jason Ren*, Russell Kunes*, Finale Doshi-Velez
Granular Motor State Monitoring of Free-Living Parkinson’s Disease Patients via Deep Learning
Kamer Ali Yuksel; Jann Goschenhofer; Hrydia V. Varna; Urban Fietzek; Franz MJ Pfister
Advancing Seq2seq Semantic Parsing with Joint Paraphrase Learning
Anonymous Authors
Analyzing the Role of Model Uncertainty for Electronic Health Records
Michael W. Dusenberry, Dustin Tran, Edward Choi, Jonas Kemp, Jeremy Nixon, Ghassen Jerfel, Katherine Heller, Andrew M. Dai
Give me (un)certainty - An exploration of parameters that affect segmentation uncertainty
Katharina V Hoebel, Ken Chang, Jay B Patel, Praveer Singh, Jayashree Kalpathy-Cramer
Accelerating Psychometric Screening Tests With Bayesian Active Differential Selection
Trevor J. Larsen; Gustavo Malkomes; Dennis L. Barbour
Semi-Supervised Histology Classification using Deep Multiple Instance Learning and Contrastive Predictive Coding
Ming Y. Lu, Richard J. Chen, Jingwen Wang, Debora Dillon, Faisal Mahmood
Synthesizing Histology Images from Molecular Profiles
Richard J Chen, Faisal Mahmood
Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant
Bora Uyumazturk, Amirhossein Kiani, Pranav Rajpurkar, Alex Wang, Robyn L. Ball, Rebecca Gao, Yifan Yu, Erik Jones, Curtis P. Langlotz, Brock Martin, Gerald J. Berry, Michael G. Ozawa, Florette K. Hazard, Ryanne A. Brown, Simon B. Chen, Mona Wood, Libby S. Allard, Lourdes Ylagan, Andrew Y. Ng, Jeanne Shen
A fully 3D multi-path convolutional neural network with feature fusion and feature weighting for automatic lesion identification in brain MRI images
Yunzhe Xue, Meiyan Xie, Fadi Farhat, Olga Boukrina, A. M. Barrett, Jeffrey R. Binder, Usman W. Roshan, William W. Graves
A Causal Inference Framework for Antidiabetic Drug Repurposing Using Observational Data from United States Electronic Health Records
Marie Charpignon*, Sudeshna Das*, Bella Vakulenko-Lagun*, Colin Magdamo*, Deborah Blacker, Yi-Han Sheu, Stan Finkelstein, Roy Welsch, Mark Albers*
Missingness as Stability: Understanding the Structure of Missingness in Longitudinal EHR data and its Impact on Reinforcement Learning in Healthcare
Scott L Fleming, Kuhan Jeyapragasan, Tony Duan, Daisy Ding, Saurabh Gombar, Nigam Shah, Emma Brunskill
A semi-supervised deep learning algorithm for abnormal EEG identification
Subhrajit Roy, Kiran Kate, Martin Hirzel
Synthetic Event Time Series Health Data Generation
Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Andrew Yale, Kristin P. Bennett
Transfer Learning of fMRI Dynamics
Usman Mahmood*, Md Mahfuzur Rahman*, Alex Fedorov*, Zening Fu, Sergey Plis
Fairness With Minimal Harm: A Pareto-Optimal Approach For Healthcare
Natalia Martinez, Martin Bertran, Guillermo Sapiro
Bayesian Recurrent Framework for Missing Data Imputation and Prediction with Clinical Time Series
Yang Guo, Zhengyuan Liu, Pavitra Krishnswamy*, Savitha Ramasamy*
Drug Repurposing for Cancer: An NLP Approach to Identify Low-Cost Therapies
Shivashankar Subramanian, Ioana Baldini, Sushma Ravichandran, Dmitriy A. Katz-Rogozhnikov, Karthikeyan Natesan Ramamurthy, Prasanna Sattigeri, Kush R. Varshney, Annmarie Wang, Pradeep Mangalath, Laura B. Kleiman
Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant
Bora Uyumazturk, Amirhossein Kiani, Pranav Rajpurkar, Alex Wang, Robyn L. Ball, Rebecca Gao, Yifan Yu, Erik Jones, Curtis P. Langlotz, Brock Martin, Gerald J. Berry, Michael G. Ozawa, Florette K. Hazard, Ryanne A. Brown, Simon B. Chen, Mona Wood, Libby S. Allard, Lourdes Ylagan, Andrew Y. Ng, Jeanne Shen
Prediction Focused Topic Models for Electronic Health Records
Jason Ren, Russell Kunes, Finale Doshi-Velez
Assessing Variance in Predictions of a Deep Learning Model to Identify Findings in Chest Radiography
John R. Zech, Jessica Z. Forde
A Biologically Plausible Benchmark for Contextual Bandit Algorithms in Precision Oncology Using in-vitro Data
Niklas Rindtorff, Nisarg Patel, MingYu Lu, Huahua Zheng, Alexander D'Amour
Pause-Focussed Sequential Modelling for Predicting Cognitive Impairment on Limited Data
Benjamin Eyre, Aparna Balagopalan, Jekaterina Novikova
Inferring the Spatial Organization of Gene Expression and Mutation from Histopathology Images using Convolutional Neural Networks
Mika S. Jain*, Tarik F. Massoud
Distributed learning in medicine: training machine learning models without sharing patient data
Anup Tuladhar, Sascha Gill, Zahinoor Ismail, Nils D. Forkert
Task incremental learning of ChestX-ray data on compact architectures
Arijit Patra, Siva M Chamarti
Integration and batch correction of scRNA-seq data with style-transfer Wasserstein Auto-Encoders
Can Ergen, Pierre Machart, Mohamed Marouf, Stefan Bonn