This review provides a comprehensive examination of the integration of Artificial Intelligence
(AI) into healthcare, focusing on its transformative implications and challenges. Utilising a …

Healthcare 4.0 is a term that has emerged recently and derived from Industry 4.0. Today, the
health care sector is more digital than in past decades; for example, spreading from x‐rays …

Over the last decade, the healthcare sector has accelerated its digitization and electronic
health records (EHRs). As information technology progresses, the notion of intelligent health …

Artificial intelligence (AI) is seen as a strategic lever to improve access, quality, and
efficiency of care and services and to build learning and value-based health systems. Many …

Artificial intelligence (AI) allows analysis of “big data” combining clinical, environmental and
laboratory based objective measures to allow a deeper understanding of sleep and sleep …

Bladder cancer has been increasing globally. Urinary cytology is considered a major
screening method for bladder cancer, but it has poor sensitivity. This study aimed to utilize …

Background Because anti-neutrophil cytoplasmatic antibody (ANCA)-associated vasculitis
(AAV) is a rare, life-threatening, auto-immune disease, conducting research is difficult but …

Objectives As the real-world electronic health record (EHR) data continue to grow
exponentially, novel methodologies involving artificial intelligence (AI) are becoming …

Sleep apnoea is now regarded as a highly prevalent systemic, multimorbid, chronic disease
requiring a combination of long‐term home‐based treatments. Optimization of personalized …

Background Assessing patient-reported outcomes (PROs) through interviews or
conversations during clinical encounters provides insightful information about survivorship …