This study aims to develop physician support software for determining ovulation time and assess its impact on pregnancy outcomes in natural cycle frozen embryo transfers (NC-FET). To develop, assess, and validate an ovulation prediction model, three ...
BACKGROUND: Mortality due to ischemic heart disease (IHD) is heterogeneously distributed globally, and identifying the sites most affected by it is essential in developing strategies to mitigate the impact of the disease, despite the complexity resul...
Annales de chirurgie plastique et esthetique
Nov 26, 2024
Peripheral facial palsy (PFP) is an alteration in the functioning of some facial muscles following an injury to the facial nerve. This pathology has functional and aesthetic consequences that impact the quality of life of patients. Their care is esse...
The Thoracic and cardiovascular surgeon
Nov 26, 2024
BACKGROUND: Lung cancer is the most prevalent and lethal cancer globally, necessitating accurate differentiation between benign and malignant pulmonary nodules to guide treatment decisions. This study aims to develop a predictive model that integrat...
European journal of obstetrics, gynecology, and reproductive biology
Nov 26, 2024
OBJECTIVE: To develop machine learning prediction models for small for gestational age with baseline characteristics and biochemical tests of various pregnancy stages individually and collectively and compare predictive performance.
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...
PURPOSE: To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).
BACKGROUND: The burden of atrial fibrillation (AF) in the intensive care unit (ICU) remains heavy. Glycaemic control is important in the AF management. Glycaemic variability (GV), an emerging marker of glycaemic control, is associated with unfavourab...
To develop and validate a machine learning (ML) model which combined computed tomography (CT) semantic and radiomics features to preoperatively predict Ki-67 expression in gastrointestinal stromal tumors (GISTs) patients. We retrospectively collected...
Journal of computer assisted tomography
Nov 25, 2024
OBJECTIVE: This study aimed to investigate the value of radiomics analysis in the precise diagnosis of triple-negative breast cancer (TNBC) based on breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and apparent diffusion coeffici...
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