Pregnancy

Comparative machine learning models for early prediction of preterm birth from maternal serum biomarkers.

BACKGROUND: Preterm birth (PTB) is a major cause of neonatal morbidity and mortality. Inflammation a...

The power of machine learning models in predicting gestational diabetes mellitus.

Features of B-mode ultrasound and contrast-enhanced ultrasound of carotid plaque based on deep learning enhance the prediction of vulnerable plaques associated with acute ischemic stroke.

OBJECTIVES: To develop an AI model using ultrasound features of carotid plaque for predicting the ri...

Inflammatory indices, machine learning and artificial intelligence in tubal ectopic pregnancy management.

OBJECTIVE: To assess the predictive value of hematologic and biochemical inflammatory indices for me...

Multimodal ultrasound and artificial intelligence for characterization of thyroid nodules in Hashimoto's thyroiditis: current challenges and future perspectives.

Patients with Hashimoto's thyroiditis (HT) frequently present with concurrent nodular lesions such a...

Nanoengineering of Exosomal Surfaces for Precision Targeting and Payload Delivery at the Molecular Level.

Exosomes, nano-sized extracellular vesicles secreted by almost all cell types, have emerged as biolo...

Deep Learning Integration of Endoscopic Ultrasound Features and Serum Data Reveals LTB4 as a Diagnostic and Therapeutic Target in ESCC.

BACKGROUND: Early diagnosis and accurate prediction of treatment response in esophageal squamous cel...

Artificial intelligence-driven nano-enhanced stem cell therapy for neurodegenerative diseases: from rational design to clinical translation.

Neurodegenerative diseases (NDs) are progressive and incurable central nervous system disorders char...

Automated Non-Invasive Burn Diagnostic System for Healthcare using Artificial Intelligence: AMBUSH-AI.

OBJECTIVE: Develop technology to predict burn wound depth using a combination of FDA approved ultras...

Novel Lipid Nanoparticle (LNP) Delivery Systems Enabling the Advancement of RNA Therapeutics.

Lipid nanoparticle (LNP)-mRNA technology has profoundly transformed the biomedical landscape, establ...

An ultrasound-based artificial intelligence framework for difficult airway prediction: A two-model, three-step decision framework.

BACKGROUND: At present, the early warning of difficult airway remains fraught with challenges. Previ...

Noninvasive Assessment of the Ulnar Nerve in the Upper Extremity Using Machine Learning.

PURPOSE: The purpose of this study was to develop a machine learning algorithm trained on ultrasound...

Artificial intelligence meets point-of-care ultrasound: implications for pediatric emergency and critical care.

PURPOSE OF REVIEW: Artificial intelligence has been integrated in nearly all aspects of clinical car...

3D deep-learning radiomics from MR-T2WI for predicting placenta accreta spectrum disorders: A multicenter study.

OBJECTIVE: To develop a three-dimensional (3D) deep-learning radiomics from magnetic resonance-T2-we...

Automated Segmentation of Stellate Ganglion Block Region in Ultrasound Images Using Deep Learning Model.

BACKGROUND: The stellate ganglion region is densely vascularized and innervated, making the stellate...

Estimating the odds ratio from the output scores of machine learning models: possibilities and limitations.

Estimation of exposure-response association is central to epidemiologic research. Although the advan...

Evaluation of AI language models in answering pregnancy-related questions assessed by obstetrics specialists.

This study aimed to compare the performance of three large language models-ChatGPT-3.5, Gemini, and ...

Small-bowel capsule endoscopy - from clinic to couch: time to go green?

PURPOSE OF REVIEW: Small-bowel capsule endoscopy (SBCE) has transformed small-intestine diagnostics ...

Artificial intelligence to support ultrasound in the detection of developmental dysplasia of the hip : a scoping review.

AIMS: Ultrasound is a highly sensitive method to detect developmental dysplasia of the hip (DDH). Ho...

Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.

Maternal postpartum depression (PPD) is a significant mental health issue that affects over 15% of m...

Corrigendum to "Predicting postpartum glucose intolerance in women with gestational diabetes mellitus in primary care: A machine learning approach using XGBoost and SHAP values" [Diabetes Res. Clin. Pract. 232 (2026) 113098].