Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic
knowledge and provides expedited solutions to complex challenges. Remarkable …

A variety of ethical concerns about artificial intelligence (AI) implementation in healthcare
have emerged as AI becomes increasingly applicable and technologically advanced. The …

Abstract Machine Learning (ML) applications are making a considerable impact on
healthcare. ML is a subtype of Artificial Intelligence (AI) technology that aims to improve the …

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)-powered service innovation (eg, OpenAI's ChatGPT, Google's Bard
and Microsoft's Sydney) has become one of the most significant determinants of firms' …

In the Internet of Medical Things (IoMT), the Internet of Things (IoT) is integrated with medical
devices, enabling improved patient comfort, cost-effective medical solutions, quick hospital …

Deep learning (DL)-based predictive models from electronic health records (EHRs) deliver
impressive performance in many clinical tasks. Large training cohorts, however, are often …

This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …

Background As a critical driving power to promote health care, the health care–related
artificial intelligence (AI) literature is growing rapidly. Objective The purpose of this analysis …

The scope of application of generative artificial intelligence (GAI) in industrial functions is
gaining high prominence in academic and industrial discourses. In this article, we explore …