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A person’s health is determined by a variety of factors beyond those captured by electronic health records or the genome. Many healthcare organizations recognize the importance of the social determinants of health (SDH) such as socioeconomic status, employment, food security, education, and community cohesion. Capturing such comprehensive portraits of patient data is necessary to transform a healthcare system and improve population health while simultaneously delivering personalized healthcare provisions. Machine learning (ML) is well-positioned to transform system-level healthcare through the design of intelligent algorithms that incorporate SDH into clinical and policy interventions, such as population health programs and clinical decision support systems. Innovations in health-tech through wearable devices and mobile health, among others, provide rich sources of data, including those characterizing SDH. The guiding metric of success should be health outcomes: the improvement of health and care at both the individual and population levels. This workshop will identify the needs of system-level healthcare transformation that ML may satisfy. We will bring together ML researchers, health policy practitioners, clinical organization experts, and individuals from all areas of clinic-, hospital-, and community-based healthcare.
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Fri 3:30 a.m. - 4:30 a.m.
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Medical Data, Synthesis, & Privacy I
(Poster Session)
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Moderator: Creighton Heaukulani Zoom join link: https://us04web.zoom.us/j/79416976497?pwd=djZNREZxUm9ON2licVVJTVYrMHpSUT09 Synthetic Tabular Data Generation with Oblivious Variational Autoencoders : Alleviating the Paucity of Personal Tabular Data for Open Research Synthesis of Time Series Physiological Data from Wearables using Deep Networks Enabling autonomous clinical decision support systems in space through AI-enhanced wearables |
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Fri 5:00 a.m. - 6:00 a.m.
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Health Systems & Delivery I
(Poster Session)
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Moderator: Creighton Heaukulani Zoom join link: https://us04web.zoom.us/j/77388399130?pwd=cXYyeE9JRXZMTy9acGVZaHVnNU5Ndz09 Interpretable Outcome Prediction with Sparse Bayesian Neural Networks in Intensive Care Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks Accurate prediction of population health costs Rapid deployment of a nationwide, one-minute, online symptoms survey during the outbreak and spread of COVID-19 - framework and applications |
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Fri 5:00 a.m. - 6:00 a.m.
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AI in Diagnosis & Therapy I
(Poster Session)
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Moderator: Konstantina Palla Zoom join link: https://us04web.zoom.us/j/74464246195?pwd=dWo3dzArYk9LcjdzZi9VbGJ4MkFDdz09 Deep Semi-Supervised Embedded Clustering (DSEC) for Stratification of Heart Failure Patients Prediction of the onset of cardiovascular diseases from electronic health records using multi-task gated recurrent units Enhancing diagnosis of tuberculosis in children with novel Mycobacterium tuberculosis antigens |
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Fri 6:30 a.m. - 8:00 a.m.
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Live Q&A Invited Speaker Panel
(Discussion Panel)
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Fri 8:30 a.m. - 9:30 a.m.
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Epidemiology & Policy I
(Poster Session)
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Moderator: Niranjani Prasad Zoom join link: https://us04web.zoom.us/j/78050144268?pwd=QnZhQ080cktHOWJvUVNuVGtDQjVWQT09 An Unsupervised Machine Learning Approach to Assess the ZIP Code Level Impact of COVID-19 in NYC In the Danger Zone: U-Net Driven Quantile Regression can Predict High-risk SARS-CoV-2 Regions via Pollutant Particulate Matter and Satellite Imagery Who Should We Test for COVID-19? A Triage Model Built from National Symptom Surveys |
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Fri 8:30 a.m. - 9:30 a.m.
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AI in Diagnosis & Therapy II
(Poster Session)
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Moderator: Konstantina Palla Zoom join link: https://us04web.zoom.us/j/76986651479?pwd=enBTaUxyR3BlV0wzcndER1h5QWJDdz09 MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas Monitoring Mental Health: Identifying Depressive and Suicidal Sentiments on Online Forums using Deep Learning Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images Identifying patterns in cystic fibrosis physiotherapy using unsupervised clustering |
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Fri 10:00 a.m. - 11:00 a.m.
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Medical Data, Synthesis, & Privacy II
(Poster Session)
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Moderator: Niranjani Prasad Zoom join link: https://us04web.zoom.us/j/74714284876?pwd=ZnNiUFVkK2RFcmdZaWdYeWZ2OU9CQT09 Patient-Reported Outcomes: A Privacy-Centric and Federated Approach to Machine Learning Benchmarking Differentially Private Residual Networks for Medical Imagery Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network |
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Fri 11:30 a.m. - 12:30 p.m.
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Health Systems & Delivery II
(Poster Session)
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Moderator: Katherine Heller Zoom join link: https://us04web.zoom.us/j/79454426445?pwd=b2F2NlJicnBGTUl6K1lsd2VQeGZmQT09 Deep Claim: Payer Response Prediction from Claims Data with Deep Learning AI-based Monitoring and Response System for Hospital Preparedness towards COVID-19 in Southeast Asia A Model is Not Enough: A case of AI-Enabled Healthcare Delivery Position Paper: IIT Kanpur Consulting Group - Using Machine Learning and Management Consulting for Social Good |
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Fri 1:00 p.m. - 2:00 p.m.
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Epidemiology & Policy II
(Poster Session)
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Moderator: Katherine Heller Zoom join link: https://us04web.zoom.us/j/72221040261?pwd=OUNuanJyTXZWRGQ4Wi8yc0w0bDErUT09 Forecasting Influenza Prevalence with Deep Transformer Models Interpretable Covid-19 Forecasting An Epidemiological Modelling Approach for Covid19 via Data Assimilation |
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Barbara Engelhardt -- Invited Talk
(Talk)
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Barbara Engelhardt 🔗 |
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Rumi Chunara -- Invited Talk
(Talk)
SlidesLive Video » |
Rumi Chunara 🔗 |
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Noa Dagan -- Invited Talk
(Talk)
SlidesLive Video » |
Noa Dagan 🔗 |
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Trishan Panch & Mohammad Jouni -- Invited Talk
(Talk)
SlidesLive Video » |
Trishan Panch 🔗 |
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Robert Morris -- Invited Talk
(Talk)
SlidesLive Video » |
Robert JT Morris 🔗 |
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Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks
(Spotlight)
SlidesLive Video » |
Emma Rocheteau 🔗 |
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Monitoring Mental Health: Identifying Depressive and Suicidal Sentiments on Online Forums using Deep Learning
(Spotlight)
SlidesLive Video » |
Meha Kumar 🔗 |
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Enabling autonomous clinical decision support systems in space through AI-enhanced wearables
(Spotlight)
SlidesLive Video » |
Eleni Antoniadou 🔗 |
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MPC-guided Imitation Learning of Neural Network Policies for the Artificial Pancreas
(Spotlight)
SlidesLive Video » |
Hongkai Chen 🔗 |
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Who Should We Test for COVID-19? A Triage Model Built from National Symptom Surveys
(Spotlight)
SlidesLive Video » |
Saar Shoer 🔗 |
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Deep Claim: Payer Response Prediction from Claims Data with Deep Learning
(Spotlight)
SlidesLive Video » |
Byung-Hak Kim 🔗 |
Author Information
Creighton Heaukulani (Ministry of Health (Singapore))
Konstantina Palla (Microsoft Research)
Katherine Heller (Duke University)
Niranjani Prasad (Princeton University)
Marzyeh Ghassemi
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