Background Artificial intelligence (AI)-based medical devices and digital health
technologies, including medical sensors, wearable health trackers, telemedicine, mobile …

Artificial intelligence tools promise transformative impacts in drug development. Regulatory
agencies face challenges in integrating AI while ensuring reliability and safety in clinical trial …

Abstract Artificial Intelligence (AI) and Machine Learning (ML) are transforming drug
discovery by overcoming traditional challenges like high costs, time-consuming, and …

Artificial intelligence (AI) and machine learning (ML) are revolutionizing the pharmaceutical
industry, particularly in drug development and delivery. These technologies enable …

Hepatitis C virus (HCV) infection affects over 71 million people worldwide, leading to severe
liver diseases, including cirrhosis and hepatocellular carcinoma. The virus's high mutation …

As the healthcare industry continues to embrace digital transformation, the Internet of
Medical Things (IoMT) emerges as a key technology. IoMT plays a critical role in …

Explainable artificial intelligence (XAI) is crucial for enhancing transparency and trust in
machine learning models, especially for tabular data used in finance, healthcare, and …

Abstract Explainable Artificial Intelligence (XAI) encompasses the strategies and
methodologies used in constructing AI systems that enable end-users to comprehend and …

In medical imaging, deep learning is a game-changing technique. It makes it possible to
accurately analyze complex medical data. We investigate the developments and difficulties …

Personalized health monitoring and prediction are indispensable in advancing healthcare
delivery, particularly amidst the escalating prevalence of chronic illnesses and the aging …