Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jun 17, 2024
Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection i...
Journal of the American Heart Association
Jun 14, 2024
BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared with prehospital stroke scales for LVO pr...
BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity.
Autism : the international journal of research and practice
May 29, 2024
Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from rout...
INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. NICU parents are twice at risk of depression symptoms compared to the general birthing population. Parental mental health problems have harmful long-te...
BACKGROUND: Early diagnosis of hypertension (HT) is crucial for preventing end-organ damage. This study aims to identify the risk factors for future HT in young individuals through the application of machine learning (ML) models.
BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and chara...
"AI-Powered Forecasting" was recently on the cover of , highlighting a new deep learning model for much faster and more accurate weather forecasting. Known as GraphCast, it outperformed the gold-standard system and had an accuracy of 99.7% for tropos...
In this narrative review, we discuss studies assessing the use of machine learning (ML) models for the early diagnosis of candidemia, focusing on employed models and the related implications. There are currently few studies evaluating ML techniques f...