The advent of machine learning (ML) and Artificial intelligence (AI) has brought about a
significant transformation across multiple industries, as it has facilitated the automation of …

Explainable AI (XAI) has the potential to transform healthcare by making AI-driven medical
decisions more transparent, reliable, and ethically compliant. Despite its promise, the …

Explainable artificial intelligence (XAI) has gained significant attention, especially in AI-
powered autonomous and adaptive systems (AASs). However, a discernible disconnect …

Machine learning (ML) is increasingly used to support or automate decision processes in
critical decision systems such as self driving cars or systems for medical diagnosis. These …

This review analyzes the application of machine learning (ML) in oncological
pharmacogenomics, focusing on customizing chemotherapy treatments. It explores how ML …

To develop more efficient catalysts and discover new materials to work towards efficient
solutions to the growing environmental problems, machine learning (ML) offers viable new …

Antimicrobial resistance (AMR) is a major threat to global public health. The current review
synthesizes to address the possible role of Artificial Intelligence and Machine Learning …

The emergence of large language models is transforming various health-related domains,
including approaches to obesity management. Obesity remains one of the world's leading …

Abstract Many industries use Machine Learning (ML) techniques to enhance systems'
performance. However, integrating ML into these systems poses challenges, often requiring …

The evolving healthcare domain necessitates an upgrade through digitization, integrating
patient data, and advanced medical results. In the last couple of decades, advances in …