Rapid advancements in artificial intelligence (AI) have revolutionized numerous sectors, including medical research. Among the various AI tools, OpenAI's ChatGPT, a state-of-the-art language model, has demonstrated immense potential in aiding and enh...
Studies in health technology and informatics
37869849
Nowadays, hospitals are facing the need for an accurate prediction of rehospitalizations. Rehospitalizations, indeed, represent both a high financial burden for the hospital and a proxy measure of care quality. The current work aims to address such a...
The integration of artificial intelligence (AI) technologies has the potential to improve both the efficiency and the quality of medical care. Applications of AI have already become established in various specialized fields in internal medicine, wher...
Rapid advances in digital technology and the promising potential of artificial intelligence (AI) are changing our everyday lives and have already impacted on hospital procedures. The use of AI applications, in particular, enables a wide range of poss...
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
38017154
The development of virtual care options, including virtual hospital platforms, is rapidly changing the healthcare, mostly in the pandemic period, due to difficulties in in-person consultations. For this purpose, in 2020, a neurological Virtual Hospit...
OBJECTIVES: Implementing ethics is crucial to prevent harm and promote widespread benefits in social experiments based on medical artificial intelligence (MAI). However, insufficient information is available concerning this within the paediatric heal...
BACKGROUND: The hospital ward system is the core service unit of a hospital and an important aspect of hospital management. The maturity of the hospital ward system represents the level of development and improvement in ward management and services. ...
Despite the dedicated research of artificial intelligence (AI) for pathological images, the construction of AI applicable to histopathological tissue subtypes, is limited by insufficient dataset collection owing to disease infrequency. Here, we prese...
BMC medical informatics and decision making
37915000
BACKGROUND: Falls are one of the most common accidents in medical institutions, which can threaten the safety of inpatients and negatively affect their prognosis. Herein, we developed a machine learning (ML) model for fall prediction in patients with...
Journal of the American Medical Informatics Association : JAMIA
37964688
OBJECTIVE: To identify factors influencing implementation of machine learning algorithms (MLAs) that predict clinical deterioration in hospitalized adult patients and relate these to a validated implementation framework.