Accepted Papers
Spotlights
"Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks". Emma Rocheteau (University of Cambridge)*; Pietro Lió (University of Cambridge); Stephanie Hyland (Microsoft Research)
[paper]
"Monitoring Mental Health: Identifying Depressive and Suicidal Sentiments on Online Forums using Deep Learning". Meha Kumar (Johns Hopkins University)*
[paper]
"Enabling autonomous clinical decision support systems in space through AI-enhanced wearables". Eleni Antoniadou (NASA FDL)*; David Belo (LIBPhys); Krittika J D'Silva (University of Cambridge); Brian Wang (NASA Frontier Development Labs); Frank Soboczenski (King's College London)
[paper]
"MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas". Hongkai Chen (Stony Brook University)*; Nicola Paoletti (Royal Holloway, University of London); Scott A. Smolka (Stony Brook University); Shan Lin (Stony Brook University)
[paper] [supplement]
"Who Should We Test for COVID-19? A Triage Model Built from National Symptom Surveys". Saar Shoer (Weizmann Institute of Science)*; Tal Karady (Weizmann Institute of Science); Ayya Keshet (Weizmann Institute of Science); Smadar Shilo (Weizmann Institute of Science); Hagai Rossman (Weizmann Institute of Science); Amir Gavrieli (Weizmann Institute of Science); Tomer Meir (Weizmann Institute of Science); Amit Lavon (Weizmann Institute of Science); Dmitry Kolobkov (Weizmann Institute of Science); Iris Kalka (Weizmann Institute of Science); Anastasia Godneva (Weizmann Institute of Science); Ori Cohen (Weizmann Institute of Science); Adam Kariv (The public knowledge workshop); Ori Hoch (The public knowledge workshop); Mushon Zer-Aviv (The public knowledge workshop); Noam Castel (The public knowledge workshop); Carole Sudre (King's College London); Anat Ekka Zohar (Maccabi Healthcare Services); Angela Irony (Maccabi Healthcare Services); Tim Spector (King's College London); Benjamin Geiger (Weizmann Institute of Science); Dorit Hizi (The public knowledge workshop); Varda Shalev (MAccabitech); Ran Balicer (Clalit Research Institute); Eran Segal (Weizmann Institute of Science)
[paper] [supplement]
"Deep Claim: Payer Response Prediction from Claims Data with Deep Learning". Byung-Hak Kim (Alpha Health)*, Seshadri Sridharan (Alpha Health), Andy Atwal (Alpha Health), Varun Ganapathi (Alpha Health)
[paper]
Posters
"An Epidemiological Modelling Approach for Covid19 via Data Assimilation". Philip Nadler (Imperial College London)*; Rossella Arcucci (Imperial College London); Shuo Wang (Imperial College London); Xian Yang (Imperial College London); Yike Guo (Imperial College London)
[paper]
"Benchmarking Differentially Private Residual Networks for Medical Imagery". Sahib Singh (OpenMined; Ford R&A)*; Harshvardhan D Sikka (OpenMined), Sasikanth Kotti (OpenMined, IIT Jodhpur), Andrew Trask (OpenMined, University of Oxford)
[paper]
"Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network". Shaoqing Yuan (Amazon)*; Parminder Bhatia (Amazon); Busra Celikkaya (Amazon); Haiyang Liu (Amazon); Kyunghwan Choi (Amazon)
[paper] [supplement]
"Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care". Hiske Overweg (Microsoft Research)*; Anna-Lena Popkes (Microsoft Research); Ari Ercole (University of Cambridge); Jose Miguel Hernandez-Lobato (University of Cambridge); Yingzhen Li (Microsoft Research Cambridge); Yordan Zaykov (Microsoft Research); Cheng Zhang (Microsoft)
[paper] [supplement]
"Rapid deployment of a nationwide, one-minute, online symtpoms survey during the outbreak and spread of COVID-19 - framework and applications". Ayya Keshet (Weizmann Institute of Science)*, Hagai Rossman (Weizmann Institute of Science), Smadar Shilo (Weizmann Institute of Science), Tomer Meir (Weizmann Institute of Science), Amir Gavrieli (Weizmann Institute of Science), Tal Karady (Weizmann Institute of Science), Saar Shoer (Weizmann Institute of Science), Anastasia Godneva (Weizmann Institute of Science), Eran Segal (Weizmann Institute of Science)
[paper]
"Identifying patterns in cystic fibrosis physiotherapy using unsupervised clustering". Tempest van Schaik (Microsoft)*, Olga Liakhovich (Microsoft), Bianca Furtuna (Microsoft), Emma Raywood, (University College London), Helen Douglas ((University College London), Kunal Kapoor (University College London), Nicole Filipow (University College London), Eleanor Main (University College London)
[paper] [supplement]
"Synthetic Tabular Data Generation with Oblivious Variational Autoencoders : Alleviating the Paucity of Personal Tabular Data for Open Research". L Vivek Harsha Vardhan (National University of Singapore)*; Stanley Kok (National University of Singapore)
[paper]
"An Unsupervised Machine Learning Approach to Assess the ZIP Code Level Impact of COVID-19 in NYC". Fadoua Khmaissia (University of Louisville)*; Pegah Sagheb Haghighi (University of Louisville ); Aarthe Jayaprakash (Syracuse University); Selina Wu (Harvard University); Sokratis Papadopoulos (New York University); Yuan Lai (Massachusetts Institute of Technology); Freddy T. Nguyen (Massachusetts Institute of Technology)
[paper]
"Synthesis of Time Series Physiological Data from Wearables using Deep Networks". Nitin Agrawal (University of Oxford)*; Max Van Kleek (University of Oxford); Nigel Shadbolt (University of Oxford)
[paper]
"Deep Semi-Supervised Embedded Clustering (DSEC) for Stratification of Heart Failure Patients". Oliver Carr (Sensyne Health); Stojan Jovanovic (Sensyne Health); Luca Albergante (Sensyne Health); Fernando Andreotti (Sensyne Health); Robert Durichen (Sensyne Health); Nadia Lipunova (Sensyne Health); Janie Baxter (Sensyne Health); Rabia Khan (Sensyne Health); Benjamin Irving (Sensyne Health)*
[paper] [supplement]
"Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units". Fernando Andreotti (Sensyne Health)*; Frank S. Heldt (Sensyne Health); Basel Abu-Jamous (Sensyne Health); Ming Li (Sensyne Health); Avelino Javer (Sensyne Health); Oliver Carr (Sensyne Health); Stojan Jovanovic (Sensyne Health); Nadia Lipunova (Sensyne Health); Benjamin Irving (Sensyne Health); Rabia Khan (Sensyne Health); Robert Durichen (Sensyne Health)
[paper] [supplement]
"AI-based Monitoring and Response System for Hospital Preparedness towards COVID-19 in Southeast Asia". Tushar Goswamy (Indian Institute of Technology, Kanpur)*; Naishadh Parmar (IIT Kanpur); Ayush Gupta (IIT Kanpur); Raunak Shah (IIT Kanpur); Vatsalya Tandon (IIT Kanpur); Varun Goyal (IIT Kanpur); Sanyog Gupta (IIT Kanpur); Karishma Laud (IIT Kanpur); Shivam Gupta (IIT Kanpur); Sudhanshu Mishra (IIT Kanpur); Ashutosh Modi (IIT Kanpur)
[paper]
"Position Paper: IIT Kanpur Consulting Group - Using Machine Learning and Management Consulting for Social Good". Tushar Goswamy (Indian Institute of Technology, Kanpur)*; Vatsalya Tandon (IIT Kanpur); Naishadh Parmar (IIT Kanpur); Raunak Shah (IIT Kanpur); Ayush Gupta (IIT Kanpur)
[paper]
"Interpretable Covid-19 Forecasting". Sercan O. Arik (Google)*; Chun-Liang Li (Google); Martin Nikoltchev (Google); Rajarishi Sinha (Google); Arkady Epshteyn (Google); Jinsung Yoon (Google); Long Le (Google); Vikas Menon (Google); Shashank Singh (Google); Yash Sonthalia (Google); Hootan Nakhost (Google); Leyou Zhang (Google); Elli Kanal (Google); Tomas Pfister (Google)
[paper]
"Forecasting Influenza Prevalence with Deep Transformer Models". Neo Wu (Google)*; Bradley Green (Google Inc.); Xue Ben (Google); Shawn O'Banion (Google)
[paper] [supplment]
"Patient-Reported Outcomes: A Privacy-Centric and Federated Approach to Machine Learning". Sara R Jordan (Future of Privacy Forum)*; Rachele Hendricks-Sturrup (Future of Privacy Forum)
[paper]
"A Model is Not Enough: A case of AI-Enabled Healthcare Delivery". Avati Anand (Stanford University)*; Sehj Kashyap (Duke Institute for Health Innovation); Margaret Smith (Stanford Healthcare); Stephanie Harman (Stanford Healthcare); Andrew Ng (Stanford University); Kenneth Jung (Stanford); Nigam Shah (Stanford); Li Ron (Stanford University)
[paper]
"Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images". Dennis H Núñez Fernández (Universidad Peruana Cayetano Heredia)*; Lamberto Ballan (University of Padova); Gabriel Jiménez Avalos (Universidad Peruana Cayetano Heredia); Jorge Coronel (Universidad Peruana Cayetano Heredia); Mirko Zimic (Universidad Peruana Cayetano Heredia)
[paper]
"In the Danger Zone: U-Net Driven Quantile Regression can Predict High-risk SARS-CoV-2 Regions via Pollutant Particulate Matter and Satellite Imagery". Jacquelyn Shelton (Hong Kong Polytechnic University)*; Przemyslaw Polewski (TomTom Location Technology Germany GmbH); Wei Yao (The Hong Kong Polytechnic University)
[paper]
"Enhancing diagnosis of tuberculosis in children with novel Mycobacterium tuberculosis antigens". Noemi Rebecca Meier (ETH Zurich); Thomas M. Sutter (ETH Zurich)*; Nicole Ritz (Universität Basel); Julia Vogt (ETH Zurich)
[paper]
"Accurate prediction of population health costs". Philipp Boss (Max Delbrück Center for Molecular Medicine)*; Dirk Enders (Institute for Applied Health Research (InGef)); Jochen Walker (Institute for Applied Health Research (InGef)); Uwe Ohler (Max Delbrück Center for Molecular Medicine)
[paper]