Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of
improving patient outcomes and optimizing healthcare delivery. By harnessing machine …

The COVID-19 pandemic has had a significant impact on both the United Arab Emirates
(UAE) and Malaysia, emphasizing the importance of developing accurate and reliable …

Abstract Objective To develop an Artificial Intelligence (AI)-based anomaly detection model
as a complement of an “astute physician” in detecting novel disease cases in a hospital and …

Background Clinical machine learning (ML) technologies can sometimes be biased and
their use could exacerbate health disparities. The extent to which bias is present, the groups …

Coronavirus disease 2019 (COVID-19) has strained healthcare systems worldwide.
Predicting COVID-19 severity could optimize resource allocation, like oxygen devices and …

OBJECTIVES: To develop and validate machine learning (ML) models to predict high-flow
nasal cannula (HFNC) failure in COVID-19, compare their performance to the respiratory …

Background Predictive models utilizing social determinants of health (SDH), demographic
data, and local weather data were trained to predict missed imaging appointments (MIA) …

Personalized drug response prediction is an approach for tailoring effective therapeutic
strategies for patients based on their tumors' genomic characterization. While machine …

Background A critical issue in the preoperative assessment of a patient with a ruptured
abdominal aortic aneurysm (rAAA) is death risk prediction. The traditional and modified …