The paper provides an overview of the development of intelligent data analysis in medicine
from a machine learning perspective: a historical view, a state-of-the-art view, and a view on …

A number of classification systems were tested on different medical data domains. Our goal
was to obtain comparative results for different methods conducted in unified manner (10-fold …

The amount of data stored in the world's databases doubles every 20 months, as estimated
by Usama Fayyad, one of the founders of machine learning and co-author of the book …

An extensive amount of information is currently available to clinical specialists, ranging from
details of clinical symptoms to various types of biochemical data and outputs of imaging …

Human healthcare is one of the most important topics for society. It tries to find the correct
effective and robust disease detection as soon as possible to patients receipt the …

Although successful in medical diagnostic problems, inductive learning systems were not
widely accepted in medical practice. In this paper two different approaches to machine …

With an increased number of medical data generated every day, there is a strong need for
reliable, automated evaluation tools. With high hopes and expectations, machine learning …

Machine learning is a novel discipline concerned with the analysis of large data and multiple
variables. It involves computationally intensive methods, is currently mainly the domain of …

Logistic regression and artificial neural networks are the models of choice in many medical
data classification tasks. In this review, we summarize the differences and similarities of …

The idea of improving medicine with computation is almost as old as digital computers. In
the early 1960s, scientists used a computer in diagnosing blood diseases, and that was just …