Artificial intelligence (AI) in the domain of healthcare is increasing in prominence.
Acceptance is an indispensable prerequisite for the widespread implementation of AI. The …

With the development of modern high-throughput omic measurement platforms, it has
become essential for biomedical studies to undertake an integrative (combined) approach to …

Background Explainability is one of the most heavily debated topics when it comes to the
application of artificial intelligence (AI) in healthcare. Even though AI-driven systems have …

Cardiovascular disease is a substantial cause of mortality and morbidity in the world. In
clinical data analytics, it is a great challenge to predict heart disease survivor. Data mining …

Artificial intelligence (AI) was first described in 1950; however, several limitations in early
models prevented widespread acceptance and application to medicine. In the early 2000s …

Artificial Intelligence (AI) has emerged as a transformative technology with immense
potential in the field of medicine. By leveraging machine learning and deep learning, AI can …

Predicting cardiac disease is considered one of the most challenging tasks in the medical
field. It takes a lot of time and effort to figure out what's causing this, especially for doctors …

Heart disease, alternatively known as cardiovascular disease, encases various conditions
that impact the heart and is the primary basis of death worldwide over the span of the past …

Providing therapies tailored to each patient is the vision of precision medicine, enabled by
the increasing ability to capture extensive data about individual patients. In this position …

Explainable artificial intelligence is an emerging research direction hel** the user or
developer of machine learning models understand why models behave the way they do …