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Workshop: MLPH: Machine Learning in Public Health

Rumi Chunara, Abraham Flaxman, Daniel Lizotte, Chirag J Patel, Laura Rosella

2020-12-12T06:00:00-08:00 - 2020-12-12T14:00:00-08:00
Abstract: Public health and population health refer to the study of daily life factors and prevention efforts, and their effects on the health of populations. We expect that work featured in this workshop will differ from Machine Learning in Healthcare as it will focus on data and algorithms related to the non-medical conditions that shape our health including structural, lifestyle, policy, social, behavior and environmental factors. Indeed, much of the data that is traditionally used in machine learning and health problems are really about our interactions with the health care system, and this workshop aims to balance this with machine learning work using data on the non-medical conditions that shape our health. There are many machine learning opportunities specific to these data and how they are used to assess and understand health and disease, that differ from healthcare specific data and tasks (e.g. the data is often unstructured, must be captured across the life-course, in different environments, etc.) This is pertinent for both infectious diseases such as COVID-19 and non-communicable diseases such as diabetes, stroke, etc. Indeed, this workshop topic is especially timely given the COVID outbreak, protests regarding racism, and associated interest in exploring relevance of machine learning to questions around disease incidence, prevention and mitigation related to both of these and their synergy. These questions require the use of data from outside of healthcare, as well as considerations of how machine learning can augment work in epidemiology and biostatistics.


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2020-12-12T05:55:00-08:00 - 2020-12-12T06:00:00-08:00
Opening Remarks - Rumi Chunara
2020-12-12T06:00:00-08:00 - 2020-12-12T06:50:00-08:00
Participatory Epidemiology and Machine Learning for Innovation in Public Health - Daniela Paolotti
Daniela Paolotti
2020-12-12T06:50:00-08:00 - 2020-12-12T07:06:00-08:00
Unsupervised Discovery of Subgroups with Anomalous Maternal and Neonatal Outcomes with WHO´s Safe Childbirth Checklist as Intervention - Girmaw Abebe Tadesse
Girmaw Abebe Tadesse
2020-12-12T07:06:00-08:00 - 2020-12-12T07:18:00-08:00
Detection of Malaria Vector Breedding Habitats using Topographic Models - Aishwarya Jadhav
Aishwarya Jadhav
2020-12-12T07:18:00-08:00 - 2020-12-12T07:28:00-08:00
AutoODE: Bridging Physics-based and Data-driven modeling for COVID-19 Forecasting - Rui Wang
Rui Wang
2020-12-12T07:28:00-08:00 - 2020-12-12T07:38:00-08:00
FireNet - Dense Forecasting of Wildfire Smoke Particulate Matter Using Sparsity Invariant CNNs - Renhao Wang
Ren Wang
2020-12-12T07:38:00-08:00 - 2020-12-12T07:40:00-08:00
Predicting air pollution spatial variation with street-level imagery - Esra Suel
Esra Suel
2020-12-12T07:40:00-08:00 - 2020-12-12T07:43:00-08:00
Automated Medical Assistance: Attention Based Consultation System - Raj Pranesh
Raj R Pranesh
2020-12-12T07:43:00-08:00 - 2020-12-12T07:48:00-08:00
A Expectation-Based Network Scan Statistic for a COVID-19 Early Warning System - Thorpe Woods
Edward Thorpe-Woods
2020-12-12T07:49:00-08:00 - 2020-12-12T07:52:00-08:00
Incorporating Healthcase Motivated Constraints in Restless Multi-Armed Bandit Based Resource Allocation - Aviva Prins
Aviva Prins
2020-12-12T07:52:00-08:00 - 2020-12-12T07:55:00-08:00
Temporal Graph Analysis for Outbreak Pattern Detection in Covid-19 Contact Tracing Networks - Dario Antweiler
Dario Antweiler
2020-12-12T07:55:00-08:00 - 2020-12-12T08:00:00-08:00
2020-12-12T08:00:00-08:00 - 2020-12-12T09:00:00-08:00
Public Health in Practice Panel: Matthew Biggerstaff (CDC), Brian DeRenzi (Dimagi), Roni Rosenfeld (CMU), Zainab Samad (AKU)
Rumi Chunara
2020-12-12T10:00:00-08:00 - 2020-12-12T10:45:00-08:00
Images and Audio Data as a Resource for Environmental Health - Scott Weichenthal
Scott Weichenthal
2020-12-12T10:45:00-08:00 - 2020-12-12T11:45:00-08:00
Speed research encounter
2020-12-12T11:45:00-08:00 - 2020-12-12T12:30:00-08:00
Understanding Big Data in Biomedicine and Public Health - Latifa Jackson
Latifa Jackson
2020-12-12T12:31:00-08:00 - 2020-12-12T12:33:00-08:00
How the COVID-19 Community Vulnerability Index (CCVI) and machine learning can enable a precision public health response to the pandemic - Nicholas Stewart
sema Sgaier
2020-12-12T12:34:00-08:00 - 2020-12-12T12:39:00-08:00
Addressing Public Health Literacy Disparities through Machine Learning: A Human in the Loop Augmented Intelligence based Tool for Public Health - Anjala Susarla
Anjana Susarla
2020-12-12T12:39:00-08:00 - 2020-12-12T12:42:00-08:00
Twitter Detects Who is Social Distancing During COVID-19 - Paiheng Xu
Paiheng Xu
2020-12-12T12:42:00-08:00 - 2020-12-12T12:45:00-08:00
Sequential Stochastic Network Structure Optimization With Applications to Addressing Canada's Obesity Epidemic - Nicholas Johnson
Nicholas Johnson
2020-12-12T12:46:00-08:00 - 2020-12-12T12:49:00-08:00
Detecting Individuals with Depressive Disorder From Personal Google Search and YouTube History Logs - Boyu Zhang
Boyu Zhang
2020-12-12T12:49:00-08:00 - 2020-12-12T12:52:00-08:00
Scalable Gaussian Process Regression Via Median Posterior Inference for Estimating Multi-Pollutant Mixture Health Effects - Aaron Sonabend
Aaron Sonabend
2020-12-12T12:52:00-08:00 - 2020-12-12T12:55:00-08:00
Steering a Historical Disease Forecasting Model Under a Pandemic: A Case of Flu and COVID-19 - Alexander Rodriguez
Alexander Rodriguez
2020-12-12T12:55:00-08:00 - 2020-12-12T13:00:00-08:00
Break 2
2020-12-12T13:00:00-08:00 - 2020-12-12T13:45:00-08:00
High Performance AI for Pandemic Prediction and Response - Madhav Marathe
Madhav Marathe
2020-12-12T13:45:00-08:00 - 2020-12-12T14:00:00-08:00
Closing remarks
Rumi Chunara