Extended Abstracts | ML4H: Machine Learning for Health

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.

Poster Session (11:30-12:30)

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

Deep Discriminative Fine-Tuning for Cancer Type Classification

Alena Harley

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

Deep Learning for the Digital Pathologic Diagnosis of Cholangiocarcinoma and Hepatocellular Carcinoma: Evaluating the Impact of a Web-based Diagnostic Assistant

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

Deep Physiological State Space Model for Clinical Forecasting

Yuan Xue

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