Background: Healthcare-associated infections are infections that patients acquire during
hospitalization or while receiving healthcare in other facilities. They represent the most …

Digital health technology (DHT) describes tools and devices that generate or process health
data. The application of DHTs could improve the diagnosis, treatment, and surveillance of …

Background Accurately predicting hospital discharge events could help improve patient flow
and the efficiency of healthcare delivery. However, using machine learning and diverse …

Hydraulic fracturing stimulation technology is essential in the oil and gas industry. However,
current techniques for predicting rock fracture pressure in hydraulic fracturing face significant …

The increasing threat of antimicrobial resistance has prompted a need for more effective
antimicrobial stewardship programs (AMS). Artificial intelligence (AI) and machine learning …

Antimicrobial resistance is recognised as one of the top threats healthcare is bound to face
in the future. There have been various attempts to preserve the efficacy of existing …

Abstract Purpose of Review This article delves into the current applications, challenges, and
future directions of artificial intelligence (AI) in healthcare epidemiology, focusing on its …

Purpose To explore the feasibility and validity of machine learning models in determining
causality in medical malpractice cases and to try to increase the scientificity and reliability of …

Nowadays, artificial intelligence in medicine plays a leading role. This necessitates the need
to ensure that artificial intelligence systems are not only high-performing but also …

Despite these challenges, the future of ML in IPC and ASP is promising, with
interdisciplinary collaboration identified as a key factor in overcoming existing barriers. ML's …