Obstetrics & Gynecology

Contrast-Invariant Self-supervised Segmentation for Quantitative Placental MRI

Accurate placental segmentation is essential for quantitative analysis of the placenta. However, this task is particularly challenging in T2*-weighted placental imaging due to: (1) weak and inconsistent boundary contrast across individual echoes; (2) the absence of manual ground truth annotations for all echo times; and (3) motion artifacts across echoes caused by fetal and maternal movement. In...

Integrated analysis of uterine leiomyosarcoma and leiomyoma utilizing TCGA and GEO data: a WGCNA and machine learning approach.

BACKGROUND: Uterine sarcoma is a gynecological mesenchymal tumor with an elusive pathogenesis. The uterine leiomyosarcoma (LMS) is the most common subtype of uterine sarcoma. LMS is a highly aggressive tumor with a poor prognosis. The genomic landscape of LMS remains unclear. Rare cases of LMS are observed to arise from leiomyoma (LM). We conducted a study to explore the genomic relationship betwe...

Three-dimensional automated segmentation of adolescent idiopathic scoliosis on computed tomography driven by deep learning: A retrospective study.

Accurate vertebrae segmentation is crucial for modern surgical technologies, and deep learning networks provide valuable tools for this task. This stu...

Intelligent deep learning model for targeted cancer drug delivery.

Nanotechnology and information communication technology (ICT) are being combined to develop innovative drug delivery systems for targeted sites, such ...

Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics.

To investigate the prediction of a model constructed by combining machine learning (ML) with clinical features and ultrasound radiomics in the clinica...

Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries.

INTRODUCTION: Informed contraceptive choice is declared when a woman selects a methods of contraceptive after receiving comprehensive information on a...

Real-time segmentation and detection of ponticulus posticus in lateral cephalometric radiographs using YOLOv8: a step towards enhanced clinical evaluation.

OBJECTIVES: Ponticulus posticus (PP) is a bony structure in the cervical spine, often difficult to identify in radiographic images, and its detection ...

Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology.

BACKGROUND: Cervical cancer remains a significant global health issue, with accurate differentiation between low-grade (LSIL) and high-grade squamous ...

Machine learning predictions of drug release from isocyanate-derived aerogels.

This work utilized machine learning (ML) algorithms to predict and validate the drug release kinetics of a short worm-like nanostructured isocyanate-...

Artificial Intelligence Tools for Preconception Cardiomyopathy Screening Among Women of Reproductive Age.

PURPOSE: Identifying cardiovascular disease before conception and in early pregnancy can better inform obstetric cardiovascular care. Our main objecti...

Cervical cancer screening uptake and its associated factor in Sub-Sharan Africa: a machine learning approach.

INTRODUCTION: Cervical cancer, which includes squamous cell carcinoma and adenocarcinoma, is a leading cause of cancer-related deaths globally, partic...

Anatomy-Guided Multitask Learning for MRI-Based Classification of Placenta Accreta Spectrum and its Subtypes

Placenta Accreta Spectrum Disorders (PAS) pose significant risks during pregnancy, frequently leading to postpartum hemorrhage during cesarean deliv...

Multimodal ultrasound-based radiomics and deep learning for differential diagnosis of O-RADS 4-5 adnexal masses.

BACKGROUND: Accurate differentiation between benign and malignant adnexal masses is crucial for patients to avoid unnecessary surgical interventions. ...

Deep learning-based model for difficult transfemoral access prediction compared with human assessment in stroke thrombectomy.

BACKGROUND: In mechanical thrombectomy (MT), extracranial vascular tortuosity is among the main determinants of procedure duration and success. Curren...

Deep Learning Enabled Segmentation, Classification and Risk Assessment of Cervical Cancer

Cervical cancer, the fourth leading cause of cancer in women globally, requires early detection through Pap smear tests to identify precancerous cha...

How might the rapid development of artificial intelligence affect the delivery of UK Defence healthcare?

Artificial intelligence (AI) has developed greatly and is now at the centre of technological advancements. Current and recent military conflicts have ...

Deep learning classification integrating embryo images with associated clinical information from ART cycles.

An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enab...

Explicating the transformative role of artificial intelligence in designing targeted nanomedicine.

INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative force in nanomedicine, revolutionizing drug delivery, diagnostics, and pers...

Automated Quality Evaluation of Cervical Cytopathology Whole Slide Images Based on Content Analysis

The ThinPrep Cytologic Test (TCT) is the most widely used method for cervical cancer screening, and the sample quality directly impacts the accuracy...

[WW domain-containing ubiquitin E3 ligase 1 regulates immune infiltration in tumor microenvironment of ovarian cancer].

OBJECTIVES: To explore the association of the expression of WW domain-containing ubiquitin E3 ligase 1 (WWP1) with immune infiltration in tumor microe...