2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) · 2022 · 18 citations · 7 references
ComputingBiomedical InformaticsHealth InformaticsClinical Decision SupportData MiningMachine LearningClassificationDecision TreesDiagnostic Decision SupportOptimization For Machine LearningPredictive Health ModelingClassification AlgorithmsDecision Tree ClassificationMachine Learning ClassificationMachine Learning Prediction ModelsMachine Learning-based ClassificationNaive BayesNaive Bayes ClassificationRandom Forest Classification
Extensive use of computer-based automation in the healthcare sector has resulted in the collection of huge amounts of digital data. Due to which, healthcare professionals find it easy to examine symptoms precisely and identify diseases at early stage but there is always certain human error. Comparatively, supervised machine learning (ML) algorithms has shown notable capability in exceeding standard approach for disease detection and helps medical experts in the early detection of high-risk diseases. In this paper, algorithms discussed were K- Nearest Neighbor, Naïve Bayes, Support Vector Machine and Decision Trees.
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