Background Machine learning (ML) is a growing field in medicine. This narrative review
describes the current body of literature on ML for clinical decision support in infectious …

Tuberculosis (TB) is an infectious disease that has been a major menace to human health
globally, causing millions of deaths yearly. Well-timed diagnosis and treatment are an arch …

Infectious diseases are caused by microorganisms belonging to the class of bacteria,
viruses, fungi, or parasites. These pathogens are transmitted, directly or indirectly, and can …

Antimicrobial resistance (AMR) is a growing public health problem in the One Health
dimension. Artificial intelligence (AI) is emerging in healthcare, since it is helpful to deal with …

Background Artificial intelligence (AI) and machine learning (ML) are poised to transform
infectious disease testing. Uniquely, infectious disease testing is technologically diverse …

The explosive growth of data in volume, velocity and diversity that are produced by medical
applications has contributed to abundance of big data. Current solutions for efficient data …

This research paper presents an overview of contemporary machine learning
methodologies and their utilization in the domain of healthcare and the prevention of …

Diagnosis, being the first step in medical practice, is very crucial for clinical decision making.
This paper investigates state-of-the-art computational intelligence (CI) techniques applied in …

In this paper, we have focused on machine learning (ML) feature selection (FS) algorithms
for identifying and diagnosing multidrug‐resistant (MDR) tuberculosis (TB). MDR‐TB is a …

Tuberculosis (TB) is among top ten causes of deaths worldwide. It is the single most cause
of deaths by an infectious disease and is ranked 2nd only after the HIV/AIDS. In third world …