Abstract: Education system plays a vital role in any one’s carrier. Students' health is an important research topic today because they are the cornerstone of our society. Researchers have used various technological breakthroughs to address schoolchildren's and college/university students' health issues, and machine learning is now frequently employed [1]. However, to understand the efficacy of machine learning and progress in student health research, a concise review of the influence of machine learning on student health is required, which the proposed work provides [3]. The primary objective is to examine which of the students' health concerns are efficiently addressed by machine learning algorithms and the outcomes of the approaches. The project also discusses what leads students to perform poorly in schools, colleges, and universities and if machine learning will improve student health in the future. The main aim of the project is to find how student health academic problems effects their performances. supervised learning algorithms applied to process the educational data and generates correlation between student health problems and academic performances. In this proposed system we develop automation for education sector [5]. Proposed system is a browser-based application meant for a college developed using Microsoft technologies such as Visual Studio, C# and SQL Server.
Keywords: mental health factor, academic performance.
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DOI:
10.17148/IJARCCE.2024.13804
