… Artificial Intelligence (AI) has recently altered the landscape of cancer research … medical
oncology using traditional Machine Learning (ML) algorithms and cutting-edge Deep Learning (…

… medical data and, in particular, there is a wide range of works done in medical diagnosis in
small-specialised diagnostic … For example, ML classifiers have been successfully applied to …

… view seem to be important for applying machine learning in medical diagnosis. In the historical
… each branch of machine learning, when applied to several medical diagnostic tasks. The …

… Machine learning has undergone significant development over the past decade and is …
is whether machine learning can be successfully applied to the field of medical diagnostics. …

… medical diagnostics. The motivation of this paper is to give an overview of the machine
learning algorithms that are applied … Bayes, logistic regression, support vector machine, K-nearest …

… diagnosis method to diagnose Heart disease for diabetic patient based on diabetes diagnosis
… The methodology described in this paper is diagnosing vulnerability of diabetic patients to …

… It is observed that over the years the use of ML in medical diagnosis has increased …
applying machine learning in medical diagnosis are considered. Articles of artificial intelligence …

… In medical diagnosis a doctor aims to explain a patient’s … However, existing machine learning
approaches to diagnosis are purely … for applying machine learning to medical diagnosis. …

… that were applied in our eligible papers. Although we say that these 12 methods are mostly
used ML methods for disease diagnosis, we limit our findings only to medical diagnosis and …

… The actual value of machine learning however depends on the ability to adapt and apply these
… In this paper we discuss two such applications for interpreting medical data for automated …