AIMC Topic: Public Health Informatics
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Machine learning in public health informatics: Evidence that complex sampling structures may not be needed for prediction models with imbalanced outcomes.
Annals of epidemiology
Jan 10, 2025
PURPOSE: The objective of this study is to investigate the predictive ability of machine learning models for imbalanced outcomes from national survey data without the use of sampling weights.
Navigating New Legal Guardrails and Emerging AI Challenges.
The Journal of law, medicine & ethics : a journal of the American Society of Law, Medicine & Ethics
Jul 12, 2024
Here, we analyze the public health implications of recent legal developments - including privacy legislation, intergovernmental data exchange, and artificial intelligence governance - with a view toward the future of public health informatics and the...
Proposing Causal Sequence of Death by Neural Machine Translation in Public Health Informatics.
IEEE journal of biomedical and health informatics
Apr 14, 2022
Each year there are nearly 57 million deaths worldwide, with over 2.7 million in the United States. Timely, accurate and complete death reporting is critical for public health, especially during the COVID-19 pandemic, as institutions and government a...
Spatio-temporal prediction of the COVID-19 pandemic in US counties: modeling with a deep LSTM neural network.
Scientific reports
Nov 5, 2021
Prediction of complex epidemiological systems such as COVID-19 is challenging on many grounds. Commonly used compartmental models struggle to handle an epidemiological process that evolves rapidly and is spatially heterogeneous. On the other hand, ma...
Clinical Predictive Models for COVID-19: Systematic Study.
Journal of medical Internet research
Oct 6, 2020
BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapid human-to-human transmission of SARS-CoV-2, many health care systems are at risk of exceeding their health care capacities, in particular in terms of...
Betacoronavirus
Pneumonia, Viral
ROC Curve
Predictive Value of Tests
Area Under Curve
Coronavirus Infections
COVID-19 Testing
Public Health Informatics
Clinical Laboratory Techniques
Hospitalization
Sensitivity and Specificity
Brazil
Respiration, Artificial
Retrospective Studies
Intensive Care Units
SARS-CoV-2
Humans
Neural Networks, Computer
Machine Learning
Pandemics
COVID-19
Algorithms
Artificial Intelligence-Empowered Mobilization of Assessments in COVID-19-like Pandemics: A Case Study for Early Flattening of the Curve.
International journal of environmental research and public health
May 14, 2020
The global outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic has uncovered the fragility of healthcare and public health preparedness and planning against epidemics/pandemics. In addition to the medical practice for treatment and immunizat...
Artificial Intelligence for Surveillance in Public Health.
Yearbook of medical informatics
Aug 16, 2019
OBJECTIVES: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.
Artificial Intelligence in Public Health and Epidemiology.
Yearbook of medical informatics
Aug 29, 2018
OBJECTIVES: To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.
Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.
International journal of medical informatics
Sep 2, 2017
PURPOSE: This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing.
Machine Learning Approaches for Detecting Diabetic Retinopathy from Clinical and Public Health Records.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Nov 5, 2015
INTRODUCTION: Annual eye examinations are recommended for diabetic patients in order to detect diabetic retinopathy and other eye conditions that arise from diabetes. Medically underserved urban communities in the US have annual screening rates that ...
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