AI-Assisted Diagnosis and Prediction of Disease in Vulnerable Populations Affected by Environmental Pollution

Madhu pandey , Dr. Santosh Kumar Singh , Kajal Mestry

Keywords: AI-Assisted Diagnosis, Environmental Health, Air Pollution Exposure, Vulnerable Population, Disease Risk Prediction, Public Health Surveillance

Abstract: Air pollution these days is, frankly, a major threat to public health—especially for vulnerable groups like children, the elderly, and individuals dealing with chronic diseases. Long-term exposure to pollutants such as PM2.5, NO2, and SO2 takes an obvious toll on these populations, exacerbating issues many already struggle with. This study presents an AI-based system designed to better diagnose and predict health conditions linked to polluted air. The framework draws on a broad range of data—air quality figures, meteorological details, population demographics, and clinical health records—to identify clear connections between pollution exposure and tangible health outcomes. By leveraging advanced machine learning techniques—Gradient Boosting, Graph Neural Networks, Multilayer Perceptron’s, you name it—the system forecasts health risks and pinpoints areas where pollutant exposure runs particularly high. The focus, unsurprisingly, sits squarely on respiratory and cardiovascular diseases, which have the strongest ties to ongoing pollution. Ultimately, the goal is a robust, real-time decision support platform that sharpens public health surveillance, enables rapid interventions, and works to protect the most at-risk communities.

Published Paper   E-Certificate

"AI-Assisted Diagnosis and Prediction of Disease in Vulnerable Populations Affected by Environmental Pollution", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 9, page no.b199-b207, September-2025, Available :https://ijsdr.org/papers/IJSDR2509127.pdf

Volume 10 Issue 9, September-2025

Pages : b199-b207

Paper Reg. ID: IJSDR_305011

Published Paper Id: IJSDR2509127

Downloads: 00080

Research Area: Health Science All

Country: mumbai, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2509127

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2509127

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition