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Israa University
2022
Computers in Biology and Medicine
Machine learning in medical applications: A review of state-of-the-art methods
145
Elsevier Ltd
105458
Information Technology, The World Islamic Sciences and Education University. Amman, Jordan; Faculty of Computer Sciences and Informatics, Amman Arab University, Amman, Jordan; School of Computer Sciences, Universiti Sains Malaysia, Pinang, Pulau, 11800, Malaysia; Department of Software Engineering, Al-Ahliyya Amman University, Amman, Jordan; Department of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah, Saudi Arabia; Department of Scientific Information and Services, Umm Al-Qura University, Mecca, Saudi Arabia; Information System College, Israa University, Gaza-Palestine, Jordan; Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, 2007, NSW, Australia
439
10.1016/j.compbiomed.2022.105458
Brain; Forecasting; Machine Learning; Reproducibility of Results; Decision making; Machine learning; Medical applications; Medical imaging; Surveys; Application area; Diagnostic systems; Environmental marketing; Machine learning methods; Machine learning models; Medical chemistry; Medical fields; Reliability performance; Standard technology; State-of-the-art methods; artificial neural network; brain; breast cancer; cancer classification; cancer diagnosis; clustering algorithm; computer prediction; decision tree; deep learning; diagnostic imaging; discriminant analysis; feature selection; gene expression; hidden Markov model; human; kernel method; lung cancer; machine learning; medicinal chemistry; neuroimaging; nonhuman; pancreas cancer; prostate cancer; Review; supervised machine learning; support vector machine; unsupervised machine learning; brain; forecasting; reproducibility; Diagnosis