Digital healthcare is transforming healthcare service models through the integration of artificial intelligence, the Internet of Things, cloud computing, big data, mobile health, digital twins, and remote monitoring technologies. These approaches enable real-time data collection, intelligent analysis, and precise decision-making for disease prevention, assisted diagnosis, personalized treatment, chronic disease management, rehabilitation, and long-term care. Digital healthcare has been widely applied in smart hospitals, remote consultation, wearable health monitoring, medical image analysis, electronic health record management, intelligent triage, and personalized health management. These applications improve medical resource utilization, enhance patient experience, and support a transition from passive treatment toward proactive prevention, continuous monitoring, and precise intervention.
Despite these advances, significant challenges remain. Medical data are highly sensitive, making privacy and security across data collection, transmission, storage, and sharing critical concerns. Inconsistent data standards and limited interoperability among medical systems, platforms, and devices also restrict efficient data circulation and collaborative use. In addition, the accuracy, fairness, transparency, and explainability of artificial intelligence algorithms require further improvement to strengthen trust among clinicians, patients, and healthcare institutions.
Research on key technologies for digital healthcare is therefore essential. Important directions include secure and trustworthy data management, privacy-preserving computing, intelligent diagnostic algorithms, edge computing, and cross-platform interoperability. Advancing these areas will support sustainable digital healthcare ecosystems and improve healthcare efficiency, personalized health management, and intelligent allocation of medical resources. This Topical Collection welcomes high-quality original research papers and review articles in digital healthcare and related interdisciplinary fields and technologies worldwide.
Association and Diagnostic Performance of PCAT Parameters Combined with Multiparametric CMR in Non-obstructive Coronary Artery Disease
jiangming zhu1,
jiani zou*2
1Department of Radiology, General Hospital of Central Theater Command of People’s Liberation Army, Graduate Joint Training Base, School of Medicine, Wuhan University of Science and Technology,
2Department of Radiology, General Hospital of Central Theater Command of People’s Liberation Army
Near-Infrared Spectroscopy for Determination of Paeoniflorin in Paeonia lactiflora Extract of Tongtian Oral Liquid
Ziliang Dong*1
1Chongqing Taiji Industrial<Group>Co., Ltd.