Public Health Upsurge: Exploring the Role of Artificial Intelligence in Diagnosing and Managing Chronic Diseases

AbstractChronic diseases such as diabetes, heart disease, cancer, and respiratory conditions are increasing globally, placing serious strain on healthcare systems—especially in low- and middle-income countries. Limited resources, underfunded infrastructure, and staff shortages make it difficult to provide timely and consistent care. As more people live with these long-term conditions, the demand for early diagnosis and continuous monitoring continues to grow. This study explores how Artificial Intelligence (AI) can support healthcare providers in managing chronic illnesses more efficiently. It focuses on practical tools such as pattern-recognition software, medical image analysis programs, and wearable devices that track patients' health. Using a quantitative approach, the research reviewed over 20,000 anonymized patient records from the United States and Brazil. It examined three common chronic conditions: type 2 diabetes, heart disease, and COPD. The study compared outcomes before and after AI tools were introduced. Findings show a 28% drop in diagnostic errors and a 22% improvement in early detection. Wearables also helped reduce hospital readmissions. However, challenges like digital inequality and data fairness remain. With proper investment and policy support, AI can greatly improve chronic care. Keyword: Artificial Intelligence, Chronic Diseases, Diagnosis, Public Health, Wearable devices, Healthcare system.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-19
DOI
https://doi.org/10.5281/zenodo.17158852
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Public Health Upsurge: Exploring the Role of Artificial Intelligence in Diagnosing and Managing Chronic Diseases

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

Public Health Upsurge: Exploring the Role of Artificial Intelligence in Diagnosing and Managing Chronic Diseases

article en

Abstract

AbstractChronic diseases such as diabetes, heart disease, cancer, and respiratory conditions are increasing globally, placing serious strain on healthcare systems—especially in low- and middle-income countries. Limited resources, underfunded infrastructure, and staff shortages make it difficult to provide timely and consistent care. As more people live with these long-term conditions, the demand for early diagnosis and continuous monitoring continues to grow. This study explores how Artificial Intelligence (AI) can support healthcare providers in managing chronic illnesses more efficiently. It focuses on practical tools such as pattern-recognition software, medical image analysis programs, and wearable devices that track patients' health. Using a quantitative approach, the research reviewed over 20,000 anonymized patient records from the United States and Brazil. It examined three common chronic conditions: type 2 diabetes, heart disease, and COPD. The study compared outcomes before and after AI tools were introduced. Findings show a 28% drop in diagnostic errors and a 22% improvement in early detection. Wearables also helped reduce hospital readmissions. However, challenges like digital inequality and data fairness remain. With proper investment and policy support, AI can greatly improve chronic care. Keyword: Artificial Intelligence, Chronic Diseases, Diagnosis, Public Health, Wearable devices, Healthcare system.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 34%
Geochemistry and Geologic Mapping
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Public Health Upsurge: Exploring the Role of Artificial Intelligence in Diagnosing and Managing Chronic Diseases · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS