Towards Applicability of Artificial Intelligence in Healthcare, Banking and Education Sector

Abstract

Machine learning is the result of a combination of computational and artificial intelligence. They use the human mind as a model to construct intelligent computers capable of solving real-world problems. It encompasses neuro computing, fuzzy logic, and genetic computing for the creation and deployment of intelligent instruments. Genetic algorithms, belief networks, and learning theory are also included in the probabilistic reasoning. Medical and genetic data classification is a fundamental problem in biomedical informatics. Small medical data categorization may be used to forecast a patient's illness state. Feature extraction or feature selection techniques may be used to minimize the size of feature sets, and then the smaller sets can be classified using effective classifiers. Using educational data mining, it is possible to predict student performance and identify pupils at risk. Using educational data mining, students' learning habits can be analyzed, growing pass rates can be boosted, and topic curriculum renewal may be maximized.. It is feasible to employ machine learning in banking for a wide range of purposes including fraud detection and improving client happiness. In this papar, we'll take a look at how machine learning is being used in the healthcare, education, and banking industries.