Infectious Disease

Public Health

Latest AI and machine learning research in public health for healthcare professionals.

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Showing 1450-1470 of 4,630 articles
Breast Cancer Detection with Standalone AI versus Radiologist Interpretation of Unilateral Surveillance Mammography after Mastectomy.

Background Limited data are available regarding the accuracy of artificial intelligence (AI) algorit...

Machine learning in cardiovascular risk assessment: Towards a precision medicine approach.

Cardiovascular diseases remain the leading cause of global morbidity and mortality. Validated risk s...

Strategies in using artificial intelligence to combat antimicrobial resistance.

Infectious diseases caused by pathogens resistant to antimicrobial treatments, defined as antimicrob...

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients wit...

Invited commentary: deep learning-methods to amplify epidemiologic data collection and analyses.

Deep learning is a subfield of artificial intelligence and machine learning, based mostly on neural ...

Global Epidemiology of Outbreaks of Unknown Cause Identified by Open-Source Intelligence, 2020-2022.

Epidemic surveillance using traditional approaches is dependent on case ascertainment and is delayed...

Hepatitis C Virus Saint Petersburg Variant Detection With Machine Learning Methods.

Hepatitis C virus infection is a significant global health concern, affecting millions worldwide. Al...

VirusImmu: a novel ensemble machine learning approach for viral immunogenicity prediction.

The viruses threats provoke concerns regarding their sustained epidemic transmission, making the dev...

A causal machine-learning framework for studying policy impact on air pollution: a case study in COVID-19 lockdowns.

When studying the impact of policy interventions or natural experiments on air pollution, such as ne...

An exploration of current and future vector-borne disease threats and opportunities for change.

Vector-borne diseases, including dengue, threaten the health and livelihoods of over 80% of the worl...

TWINVAX: conceptual model of a digital twin for immunisation services in primary health care.

INTRODUCTION: This paper presents a proposal for the modelling and reference architecture of a digit...

IoT and ML-driven framework for managing infectious disease risks in communal spaces: a post-COVID perspective.

COVID-19 has not only changed the way people live but has also altered the way all organizations ope...

Artificial intelligence in vaccine research and development: an umbrella review.

BACKGROUND: The rapid development of COVID-19 vaccines highlighted the transformative potential of a...

Anomaly recognition in surveillance based on feature optimizer using deep learning.

Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet exis...

Advancing Early Warning Systems for Malaria: Progress, challenges, and future directions - A scoping review.

Malaria Early Warning Systems (EWS) are predictive tools that often use climatic and other environme...

What drives the effectiveness of social distancing in combating COVID-19 across U.S. states?

We propose a new theory of information-based voluntary social distancing in which people's responses...

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