Application of Machine Learning Algorithms: An Exploratory Study in Skin Lesion Prediction

• Grant number: 24/10989-4
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Engineering - Production Engineering
• Principal Investigator: Lucas Daniel Del Rosso Calache
• Grantee: Luisa Brolacci Lana
• Host Institution: Faculdade de Engenharia. Universidade Estadual Paulista (UNESP). Campus Experimental São João da Boa Vista. São João da Boa Vista , SP, Brazil

Abstract

In a world where processes in general are increasingly multifaceted and interconnected, it is essential to use robust analytical tools to solve complex problems in different contexts and sectors, such as: market and resource management, risk analysis, demand forecasting, optimization of production processes, diagnosis of system failures, reduction of operating costs, among others. One of the solutions to this demand is the use of machine learning technology through the implementation of an algorithm capable of analyzing heterogeneous data and predicting results in various scenarios. The aim of this scientific initiation project is to select and validate a machine learning model that, by identifying patterns among the data analyzed and correlating different variables, achieves adequate performance in predicting results. To achieve this goal, the project will follow a series of steps, including an exploratory review of the literature on machine learning techniques and their applications in the health area; the selection of techniques for implementation and; the pilot application of the algorithms in the prospective identification of skin lesions in pediatric critical patients. The development of this project aims to improve knowledge about the implementation of machine learning in the form of a predictive model that assists in the decision-making process of healthcare professionals, promoting the effective use of decision support techniques to prevent skin lesions among patients, contributing to reducing the risk of this unnecessary damage associated with healthcare and proposing an innovative and effective method for dealing with this problem.