Latest AI and machine learning research in health policy for healthcare professionals.
Water scarcity poses a significant global challenge, particularly in developing nations like Iran. Consequently, there is a pressing requirement for ongoing monitoring and prediction of water quality, utilizing advanced techniques characterized by low implementation costs, shorter timeframes, and high accuracy. In the present study, the investigation and forecasting of the monthly time series of a...
This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical cas...
As population density increases, environmental hygiene and public health become increasingly severe. As the space where residents stay for the longest...
BACKGROUND: Chronic kidney disease is a prevalent global health issue, particularly in advanced stages requiring dialysis. Vascular access (VA) qualit...
While one can characterize mental health using questionnaires, such tools do not provide direct insight into the underlying biology. By linking approa...
Simulation models and artificial intelligence (AI) are largely used to address healthcare and biomedical engineering problems. Both approaches showed ...
Tools based on artificial intelligence (AI) are currently revolutionising many fields, yet their applications are often limited by the lack of suitabl...
Artificial intelligence revolutionizes nursing informatics and healthcare by enhancing patient outcomes and healthcare access while streamlining nursi...
"Garbage in, garbage out" summarises well the importance of high-quality data in machine learning and artificial intelligence. All data used to train ...
Electronic health records (EHRs) store an extensive array of patient information, encompassing medical histories, diagnoses, treatments, and test outc...
INTRODUCTION: Nurses' innovative behaviours play a crucial role in addressing the challenges including adapting to emerging technologies, resource lim...
Large language models (LLMS)Â emerge as the most promising Natural Language Processing approach for clinical practice acceleration (i.e., diagnosis, pr...
The surgical robot is assumed to be a fixed, indirect cost. We hypothesized rising volume of robotic bariatric procedures would decrease cost per pati...
With the increasing prevalence of artificial intelligence (AI) and other digital technologies in healthcare, the ethical debate surrounding their adop...
This article presents a novel hardware-assisted distributed ledger-based solution for simultaneous device and data security in smart healthcare. This ...
Accurate prediction of water quality contributes to the intelligent management of water resources. Water quality indices have time series characterist...
The healthcare sector, characterized by vast datasets and many diseases, is pivotal in shaping community health and overall quality of life. Tradition...
Internet of Medical Things (IoMT) is an emerging subset of Internet of Things (IoT), often called as IoT in healthcare, refers to medical devices and ...
The use of robots has revolutionized healthcare, wherein further innovations have led to improved precision and accuracy. Conceived in the late 1960s,...
The integration of machine/deep learning and sensing technologies is transforming healthcare and medical practice. However, inherent limitations in he...