Obstetrics & Gynecology

Employing machine learning models to predict pregnancy termination among adolescent and young women aged 15-24 years in East Africa.

Pregnancy termination is still a sensitive and continuing public health issue due to several political, economic, religious, and social concerns. This study assesses the applications of machine learning models in the prediction of pregnancy termination using data from eleven national datasets in East Africa. Nine machine learning models, namely: Random Forests (RF), Decision Tree, Logistic Regress...

Comparative evaluation of ChatGPT-4, ChatGPT-3.5 and Google Gemini on PCOS assessment and management based on recommendations from the 2023 guideline.

CONTEXT: Artificial intelligence (AI) is increasingly utilized in healthcare, with models like ChatGPT and Google Gemini gaining global popularity. Polycystic ovary syndrome (PCOS) is a prevalent condition that requires both lifestyle modifications and medical treatment, highlighting the critical need for effective patient education. This study compares the responses of ChatGPT-4, ChatGPT-3.5 and ...

anti-cancer activity of siddha metallo-mineral formulation from Thanga uram with Hela cell lines.

The second most common malignant tumour in women worldwide, cervical cancer seriously jeopardizes their health. It has been established that a high-ri...

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using an AI Chatbot as a Genetic Counselor: Clinical Study.

BACKGROUND: Hereditary breast and ovarian cancer (HBOC) is a major type of hereditary cancer. Establishing effective screening to identify high-risk i...

Improved clinical pregnancy rates in natural frozen-thawed embryo transfer cycles with machine learning ovulation prediction: insights from a retrospective cohort study.

This study aims to develop physician support software for determining ovulation time and assess its impact on pregnancy outcomes in natural cycle froz...

A lightweight deep learning method to identify different types of cervical cancer.

Cervical cancer is the second most common cancer in women's bodies after breast cancer. Cervical cancer develops from dysplasia or cervical intraepith...

A Study on Automatic O-RADS Classification of Sonograms of Ovarian Adnexal Lesions Based on Deep Convolutional Neural Networks.

OBJECTIVE: This study explored a new method for automatic O-RADS classification of sonograms based on a deep convolutional neural network (DCNN).

Artificial intelligence chatbots versus traditional medical resources for patient education on "Labor Epidurals": an evaluation of accuracy, emotional tone, and readability.

BACKGROUND: Labor epidural analgesia is a widely used method for pain relief in childbirth, yet information accessibility for expectant mothers remain...

Deep learning model for the automated detection and classification of central canal and neural foraminal stenosis upon cervical spine magnetic resonance imaging.

BACKGROUND: A deep learning (DL) model that can automatically detect and classify cervical canal and neural foraminal stenosis using cervical spine ma...

Exploring acetylation-related gene markers in polycystic ovary syndrome: insights into pathogenesis and diagnostic potential using machine learning.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is a prevalent cause of menstrual irregularities and infertility in women, impacting quality of life. Desp...

Deep learning model using continuous skin temperature data predicts labor onset.

BACKGROUND: Changes in body temperature anticipate labor onset in numerous mammals, yet this concept has not been explored in humans. We investigated ...

Exploratory study on the enhancement of O-RADS application effectiveness for novice ultrasonographers via deep learning.

PURPOSE: The study aimed to create a deep convolutional neural network (DCNN) model based on ConvNeXt-Tiny to identify classic benign lesions (CBL) fr...

Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation.

Cervical cancer is one of the biggest challenges in global health, thus it forms a critical need for early detection technologies that could improve p...

Development of an Artificial Intelligence-Based Algorithm for the Assessment of Skeletal Age and Detection of Cervical Vertebral Anomalies in Patients with Cleft Lip and Palate.

ObjectiveTo develop an artificial intelligence (AI)-based algorithm for the assessment and comparison of skeletal maturation in patients with and with...

CDSNet: An automated method for assessing growth stages from various anatomical regions in lateral cephalograms based on deep learning.

BACKGROUND: The assessment of growth stages, typically determined by Cervical Vertebrae Maturation (CVM), plays a crucial role in orthodontics. Howeve...

Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.

Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in ...

Configurational analysis of ovarian cancer incidence in 30 provinces of China and its policy implications: a fuzzy-set qualitative comparative analysis approach.

INTRODUCTION: Ovarian cancer is one of the three most common gynecological cancers, with the highest mortality rate among gynecological malignancies. ...

Performance of a Full-Coverage Cervical Cancer Screening Program Using on an Artificial Intelligence- and Cloud-Based Diagnostic System: Observational Study of an Ultralarge Population.

BACKGROUND: The World Health Organization has set a global strategy to eliminate cervical cancer, emphasizing the need for cervical cancer screening c...

HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment.

BACKGROUND: Accurate measurement of the hip-knee-ankle (HKA) angle is essential for informed clinical decision-making in the management of knee osteoa...

Machine learning for classifying chronic ankle instability based on ankle strength, range of motion, postural control and anatomical deformities in delivery service workers with a history of lateral ankle sprains.

OBJECTIVE: Chronic ankle instability (CAI) frequently develops as a result of lateral ankle sprains (LAS) in delivery service workers (DSWs). Identify...