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Machine Learning-Based Risk Prediction for Diabetes Using Health Survey and Clinical Indicators

Year: 2024

Type: article

Abstract: The increasing global burden of diabetes necessitates proactive data-driven methods for risk detection and management. This research explores a comprehensive dataset of 35 health indicators—covering demographics, laboratory results, and lifestyle variables—to identify patterns related to diabetes occurrence. Employing multiple machine learning models, the study evaluates key predictors such as BMI, age, blood pressure, and physical activity. Results highlight the potential of these models in supporting targeted interventions and strengthening public health strategies

Source: International Journal of Advanced Research in Science Communication and Technology

DOI: 10.48175/ijarsct-19700j

Authors: Dr. Prem Kumar Chandrakar, Simaran Chandrakar

Language: English

Topic: Artificial Intelligence in Healthcare

Subfield: Health Information Management

Field: Health Professions

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4410914759

FWCI:

Cites: 4

Cited by:

Related to: 10