Obstetrics & Gynecology

Artificial intelligence for cervical cancer screening: Scoping review, 2009-2022.

BACKGROUND: The intersection of artificial intelligence (AI) with cancer research is increasing, and many of the advances have focused on the analysis of cancer images.

Performance of a multidisciplinary robotic surgery program at a university hospital (2012-2022).

Robotic-assisted surgery has become widely adopted for its ability to expand the indications for minimally invasive procedures. This technology aims to improve precision, accuracy, and outcomes while reducing complications, blood loss, and recovery time. Successful implementation of a robotic surgery program requires careful initial design and a focus on maintenance and expansion to maximize its b...

Hybrid chain reaction and selective recognition-based homogeneous dual-fluorescence analysis of circulating tumor cells in clinical ovarian cancer samples.

BACKGROUND: Oncological analysis is important in tumor diagnosis. We constructed a dual-fluorescence and binary visual analysis system for circulating...

Pediatric Psoriasis Associated with Van Wyk Grumbach Syndrome: A case report.

INTRODUCTION: Psoriasis is a common chronic inflammatory condition, often beginning in childhood in approximately one-third of cases. It can be associ...

MLNet: Metaheuristics-Based Lightweight Deep Learning Network for Cervical Cancer Diagnosis.

One of the leading causes of cancer-related deaths among women is cervical cancer. Early diagnosis and treatment can minimize the complications of thi...

Automation and artificial intelligence in radiation therapy treatment planning.

Automation and artificial intelligence (AI) is already possible for many radiation therapy planning and treatment processes with the aim of improving ...

Improved precise guidewire delivery of a cardiovascular interventional surgery robot based on admittance control.

PURPOSE: The development of cardiovascular interventional surgery robots can realize master-slave interventional operations, which will effectively so...

Normal intellectual ability and hyperprolactinemia as unique clinical manifestations of congenital hypothyroidism: A case report and review of hypotheses.

Congenital hypothyroidism is the deficiency of thyroid hormone in infants and hyperprolactinemia is frequently observed. Previously reported cases typ...

Cervical cell's nucleus segmentation through an improved UNet architecture.

Precise segmentation of the nucleus is vital for computer-aided diagnosis (CAD) in cervical cytology. Automated delineation of the cervical nucleus ha...

Prenatal diagnosis of hypoplastic left heart syndrome on ultrasound using artificial intelligence: How does performance compare to a current screening programme?

BACKGROUND: Artificial intelligence (AI) has the potential to improve prenatal detection of congenital heart disease. We analysed the performance of t...

An intelligent adverse delivery outcomes prediction model based on the fusion of multiple obstetric clinical data.

Adverse delivery outcomes is a major re-productive health problem that affects the physical and mental health of pregnant women. Obviously, obstetric ...

CURRENT NEURAL NETWORKS DEMONSTRATE POTENTIAL IN AUTOMATED CERVICAL VERTEBRAL MATURATION STAGE CLASSIFICATION BASED ON LATERAL CEPHALOGRAMS.

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Neural networks for classification of cervical vertebrae maturation: a systematic review. Mathew R, Palat...

Computer-aided diagnosis for screening of lower extremity lymphedema in pelvic computed tomography images using deep learning.

Lower extremity lymphedema (LEL) is a common complication after gynecological cancer treatment, which significantly reduces the quality of life. While...

Safety and Accuracy of Robot-Assisted Cervical Screw Placement: A Systematic Review and Meta-Analysis.

OBJECTIVE: The purpose of this study was to compare the accuracy and safety of robot-assisted (RA) cervical screw placement with conventional freehand...

Analysis of Prospective Genetic Indicators for Prenatal Exposure to Arsenic in Newborn Cord Blood of Using Machine Learning.

Using a machine learning methods, we aim to find biological effect biomarkers of prenatal arsenic exposure in newborn cord blood. From the Gene Expres...

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an a...

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

INTRODUCTION: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed lead...

Comparison of the carotid corrected flow time and tidal volume challenge for assessing fluid responsiveness in robot-assisted laparoscopic surgery.

We aimed to compare the ability of carotid corrected flow time assessed by ultrasound and the changes in dynamic preload indices induced by tidal volu...

Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers.

BACKGROUND: In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dos...

Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers.

High-grade serous ovarian cancer is the most lethal gynaecological malignancy. Detailed molecular studies have revealed marked intra-patient heterogen...