AIMC Topic: Public Health

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Introduction to WBE case estimation: A practical toolset for public health practitioners.

The Science of the total environment
Public health practitioners can use wastewater data to grasp disease dynamics, including incidence, prevalence, and potential disease trajectory. The expertise required to analyze and interpret wastewater data exceed those of most entry-level epidemi...

Comparison of dynamic mode decomposition with other data-driven models for lung cancer incidence rate prediction.

Frontiers in public health
INTRODUCTION: Public health data analysis is critical to understanding disease trends. Existing analysis methods struggle with the complexity of public health data, which includes both location and time factors. Machine learning offers powerful tools...

Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance.

Scientific reports
Currently, antimicrobial resistance (AMR) poses a major public health challenge. The emergence of AMR, which significantly threatens public health, is primarily due to the overuse of antimicrobial agents. This study explored the possibility that the ...

Advancing Pedagogy in Leadership Practice to Enhance Public Health Impact.

Journal of public health management and practice : JPHMP
BACKGROUND: The COVID-19 pandemic highlighted the critical need for competent leadership in public health to address emergent health challenges and restore trust in health institutions. Emphasizing leadership training in public health education progr...

Antimicrobial resistance: Linking molecular mechanisms to public health impact.

SLAS discovery : advancing life sciences R & D
BACKGROUND: Antimicrobial resistance (AMR) develops into a worldwide health emergency through genetic and biochemical adaptations which enable microorganisms to resist antimicrobial treatment. β-lactamases (blaNDM, blaKPC) and efflux pumps (MexAB-Opr...

Precision in Prevention and Health Surveillance: How Artificial Intelligence May Improve the Time of Identification of Health Concerns through Social Media Content Analysis.

Yearbook of medical informatics
OBJECTIVE: To explore how artificial intelligence (AI) methodologies, particularly through the analysis of social media content, can enhance "precision in prevention and health surveillance" (2024 Yearbook topic). The focus is on leveraging advanced ...

Artificial intelligence strategies based on random forests for detection of AI-generated content in public health.

Public health
OBJECTIVES: To train and test a Random Forest machine learning model with the ability to distinguish AI-generated from human-generated textual content in the domain of public health, and public health policy.

The Emergence of AI in Public Health Is Calling for Operational Ethics to Foster Responsible Uses.

International journal of environmental research and public health
This paper discusses the responsible use of artificial intelligence (AI) in public health and in medicine, and questions the development of AI ethics in international guidelines from a public health perspective. How can a global ethics approach help ...

The generative revolution: AI foundation models in geospatial health-applications, challenges and future research.

International journal of health geographics
In an era of rapid technological advancements, generative artificial intelligence and foundation models are reshaping industries and offering new advanced solutions in a wide range of scientific areas, particularly in public and environmental health....

[Artificial intelligence in Public Health: opportunities, ethical challenges and future perspectives].

Revista espanola de salud publica
Artificial Intelligence (AI) is transforming Public Health by providing innovative tools to address complex global challenges. Its ability to analyze large volumes of data in real time enhances epidemiological surveillance, optimizes healthcare resou...