A Statistical Review on Machine Learning based Medical Diagnostic Systems

Abstract

In the case of diagnosis of any particular disease, it is very complex and difficult to make an adequate
and appropriate decision. There are several confusions and complications in the process of diagnosis
by using the human visual system, and these loopholes further result in making decisions that might
be improper and irrelevant for a specific diagnosis. These limitations are overcome by using effective
machine learning techniques, which assist the physician to provide top-notch and accurate treatment to
the patient. The publications by numerous researchers are rapidly increasing, which assisted to know
about the utilization of machine learning technologies in the medical domain. The main intent of this
paper is to statistically review the various research works done to develop the medical diagnostic
system by using machine learning. This study also aids to identify the effective enhancement in
several domains of medicals by utilizing the efficient methodologies of machine learning. The
selected research work is also classified on the basis of some criteria such as year of publication, the
objective of research work, journal type, the used input as well as output by the researcher, research
gap and result provided by the author after providing the finding on respective research gap. This
paper also explained the significance of machine learning techniques in the medical field. Moreover,
the predicted result assist in identifying the number of ways which can be utilized to implement the
methodologies of machine learning, which further help the professionals or experts to accomplish the
objective successfully and to acquire the desired output.