Abstract Machine learning is as growing as fast as concepts such as Big data and the field of
data science in general. The purpose of the systematic review was to analyze scholarly …

In the field of cancer genomics, the broad availability of genetic information offered by next-
generation sequencing technologies and rapid growth in biomedical publication has led to …

Supervised and unsupervised learning algorithms have shown a great potential in
knowledge acquisition from large data sets. Supervised learning reflects the ability of an …

Analysis of microarray data is a highly challenging problem due to the inherent complexity in
the nature of the data associated with higher dimensionality, smaller sample size …

Background/objectives In the current scenario, artificial intelligence (AI) is going to change
almost all the areas of the medical field. The need is to study the research carried out in this …

Neural networks are powerful tools used widely for building cancer prediction models from
microarray data. We review the most recently proposed models to highlight the roles of …

Objective To provide a state of the art review of artificial intelligence (AI), including its
subfields of machine learning and natural language processing, as it applies to …

Precision medicine in oncology aims at obtaining data from heterogeneous sources to have
a precise estimation of a given patient's state and prognosis. With the purpose of advancing …

The United Arab Emirates (UAE) has recently focused on implementing Artificial Intelligence
(AI) projects in the government healthcare sector to help manage chronic diseases and early …

Background and objective: Cancer has become a complex health problem due to its high
mortality. Over the past few decades, with the rapid development of the high-throughput …