AIMC Topic: Female

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Machine learning for the prediction of spontaneous preterm birth using early second and third trimester maternal blood gene expression: A cautionary tale.

PloS one
Spontaneous preterm birth (sPTB) remains a significant global health challenge and a leading cause of neonatal mortality and morbidity. Despite advancements in neonatal care, the prediction of sPTB remains elusive, in part due to complex etiologies a...

Comparison of machine learning and validation methods for high-dimensional accelerometer data to detect foot lesions in dairy cattle.

PloS one
Lameness is one of the major production diseases affecting dairy cattle. It is associated with negative welfare in affected cattle, economic losses at the farm level, and adverse effects on sustainability. Prompt identification of lameness is necessa...

3Mont: A multi-omics integrative tool for breast cancer subtype stratification.

PloS one
Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types among women. Developing effective treatment strategies that address diverse types of BRCA is crucial. Notably, among different BRCA molecular sub-types,...

Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments.

BMJ health & care informatics
OBJECTIVE: Machine learning (ML) models have emerged as tools to predict length of stay (LOS) and disposition decision (DD) in emergency departments (EDs) to combat overcrowding. However, site-specific ML models are not transferable to different site...

Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.

Pediatric surgery international
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...

Prognostic predictions in psychosis: exploring the complementary role of machine learning models.

BMJ mental health
BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practi...

Exploring semantic grounding in the posterior parietal cortex.

Brain structure & function
This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system to one that recognizes the involvement of dynamic, distributed neural networks. Recent evidence sup...

From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.

World journal of urology
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...

Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.

Heart (British Cardiac Society)
BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is in direct contact with the left ventricular myocardium. While it is associated with coronary artery disease, little is known regarding its role in aort...