A Proposed Framework for Disease Prediction Using Machine Learning Techniques (FDPMLT)
Keywords:
Disease, Prediction, Machine Learning, FdmltAbstract
A lot of people are interested in how machine learning may be used in healthcare, as it could help with illness prediction and prevention. Disease Prediction using Machine Learning Techniques (FDMLT) is a new framework that aims to improve disease prediction models in terms of accuracy and efficiency. It is introduced in this study. To build reliable prediction models, the suggested framework makes use of a wide variety of machine learning algorithms, data pretreatment approaches, and feature engineering methodologies. In the first step of the framework, several healthcare datasets are thoroughly investigated. These datasets include clinical factors, genetic information, and patient records. After then, the data is painstakingly prepared for analysis by means of cleaning, normalisation, and imputation to guarantee the dataset's integrity and accuracy. In order to improve the model's predictive potential, feature engineering approaches are used to extract pertinent data and generate useful features.
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