Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
Jun 3, 2024
OBJECTIVE: Although remarkable strides have been made in fetal medicine and the prenatal diagnosis of congenital heart disease, around 60% of newborns with isolated coarctation of the aorta (CoA) are not identified prior to birth. The prenatal detect...
BACKGROUND AND PURPOSE: Intracranial hemorrhage (ICH) in leukemia patients progresses rapidly with high mortality. Limited data are available on imaging studies in this population. The study aims to develop prediction models for 7-day and short-term ...
South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde
May 31, 2024
BACKGROUND: Artificial intelligence (AI), using deep learning (DL) systems, can be utilised to detect radiological changes of various pulmonary diseases. Settings with a high burden of tuberculosis (TB) and people living with HIV can potentially bene...
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.
PURPOSE: To investigate the potential of an Optical Coherence Tomography (OCT) based Deep-Learning (DL) model in the prediction of Vitreomacular Traction (VMT) syndrome outcomes.
Nutrition, metabolism, and cardiovascular diseases : NMCD
May 29, 2024
AIM: Machine learning may be a tool with the potential for obesity prediction. This study aims to review the literature on the performance of machine learning models in predicting obesity and to quantify the pooled results through a meta-analysis.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
May 29, 2024
OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing both the intratumoral and peritumoral-to predict the status of axillary lymph nodes in patients with...
PURPOSE OF REVIEW: Machine learning (ML) approaches are an emerging alternative for healthcare risk prediction. We aimed to synthesise the literature on ML and classical regression studies exploring potential prognostic factors and to compare predict...
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.
AIM: The objective of this study was to create and authenticate a prognostic model for lymph node metastasis (LNM) in colorectal cancer (CRC) that integrates clinical, radiomics, and deep transfer learning features.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.