Obstetrics & Gynecology

Distinguishing the Uterine Artery, the Ureter, and Nerves in Laparoscopic Surgical Images Using Ensembles of Binary Semantic Segmentation Networks.

Performing a minimally invasive surgery comes with a significant advantage regarding rehabilitating ...

Evaluating the Quality of Postpartum Hemorrhage Nursing Care Plans Generated by Artificial Intelligence Models.

BACKGROUND: With the rapidly advancing technological landscape of health care, evaluating the potent...

Leveraging Artificial Intelligence to Revolutionize Ovarian Cancer Diagnosis.

Precision in Prevention: Tailoring Single-Use Negative Pressure Wound Therapy Utilization Through Artificial Intelligence-Based Surgical Site Complications Risk and Cost Modeling.

Surgical site complications (SSCs) are common, yet preventable hospital-acquired conditions. Single...

Preoperative CECT-Based Multitask Model Predicts Peritoneal Recurrence and Disease-Free Survival in Advanced Ovarian Cancer: A Multicenter Study.

RATIONALE AND OBJECTIVES: Peritoneal recurrence is the predominant pattern of recurrence in advanced...

Automated Machine Learning and Explainable AI (AutoML-XAI) for Metabolomics: Improving Cancer Diagnostics.

Metabolomics generates complex data necessitating advanced computational methods for generating biol...

Machine learning models for prediction of postoperative venous thromboembolism in gynecological malignant tumor patients.

AIM: To identify risk factors that associated with the occurrence of venous thromboembolism (VTE) wi...

Fetal bladder rupture after high-dose maternal opioid treatment: a case report.

OBJECTIVES: Fetal bladder rupture is rare and mainly caused by lower urinary tract obstruction (LUTO...

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weigh...

Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with...

Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis.

This comprehensive review investigates the transformative potential of sensor-driven digital twin te...

A lightweight hybrid model for the automatic recognition of uterine fibroid ultrasound images based on deep learning.

PURPOSE: Uterine fibroids (UF) are the most frequent tumors in ladies and can pose an enormous threa...

Experience of Using Neural Networks to Assess Age-Related Changes in Some Structures of the Skull and Cervical Vertebrae Based on CT Scans (Pilot Project).

UNLABELLED: is to study the possibility of using artificial intelligence technologies for age predi...

Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML)...

Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction.

The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-D...

Cervical wear pathobiology by robot-simulated 3-year toothbrushing - New methodological approach.

OBJECTIVES: An ex-vivo study was aimed at (i) programming clinically validated robot three-year rand...

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

OBJECTIVE:  To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Goo...

Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body...

Use of natural language processing to uncover racial bias in obstetrical documentation.

Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinica...

Construction of deep learning-based convolutional neural network model for automatic detection of fluid hysteroscopic endometrial micropolyps in infertile women with chronic endometritis.

OBJECTIVE(S): Chronic endometritis (CE) is a localized mucosal inflammatory disorder associated with...

Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning.

Predicting the probability of having the plan approved by the physician is important for automatic t...