Software engineering health data prediction: Application of health Systems using machine learning
DOI:
https://doi.org/10.48047/Keywords:
Software engineering, Machine learning, health informatic, Indian Diabetes dataset, extreme learning machine.Abstract
Recently, machine learning has become a hot research topic. Therefore, this study investigates the interaction between software engineering and machine learning within the context of health systems. We proposed a novel framework for health informatics: the framework and methodology of software engineering for machine learning in health informatics (SEMLHI). The SEMLHI framework includes four modules (software, machine learning, machine learning algorithms, and health informatics data) that organize the tasks in the framework using a SEMLHI methodology, thereby enabling researchers and developers to analyze health informatics software from an engineering perspective and providing developers with a new road map for designing health applications with system functions and software implementations.
