Obstetrics & Gynecology

Deep learning algorithm to evaluate cervical spondylotic myelopathy using lateral cervical spine radiograph.

BACKGROUND: Deep learning (DL) is an advanced machine learning approach used in different areas such as image analysis, bioinformatics, and natural language processing. A convolutional neural network (CNN) is a representative DL model that is highly advantageous for imaging recognition and classification This study aimed to develop a CNN using lateral cervical spine radiograph to detect cervical s...

Automatic measurement of fetal head circumference using a novel GCN-assisted deep convolutional network.

The growth of the fetus can be effectively monitored by measuring the fetal head circumference (HC) in ultrasound images. Moreover, it is the key to assessing the fetus's health. Ultrasound fetal head image boundary is blurred. The ultrasound sound shadow results in a partial absence of the skull in the image. The amniotic fluid and uterine wall form a structure similar to the head texture and gra...

Cervical optical coherence tomography image classification based on contrastive self-supervised texture learning.

BACKGROUND: Cervical cancer (CC) seriously affects the health of the female reproductive system. Optical coherence tomography (OCT) emerged as a nonin...

Deep Learning Prediction of Ovarian Malignancy at US Compared with O-RADS and Expert Assessment.

Background Deep learning (DL) algorithms could improve the classification of ovarian tumors assessed with multimodal US. Purpose To develop DL algorit...

Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis.

The integration of artificial intelligence in precision medicine has revolutionized healthcare delivery. Precision medicine identifies the phenotype o...

SRAS-net: Low-resolution chromosome image classification based on deep learning.

Prenatal karyotype diagnosis is important to determine if the foetus has genetic diseases and some congenital diseases. Chromosome classification is a...

Prediction of low Apgar score at five minutes following labor induction intervention in vaginal deliveries: machine learning approach for imbalanced data at a tertiary hospital in North Tanzania.

BACKGROUND: Prediction of low Apgar score for vaginal deliveries following labor induction intervention is critical for improving neonatal health outc...

Functionalized Spiral-Rolling Millirobot for Upstream Swimming in Blood Vessel.

Untethered small robots with multiple functions show considerable potential as next-generation catheter-free systems for biomedical applications. Howe...

Development of an affordable, immersive model for robotic vaginal cuff closure: a randomized trial.

Safe and secure closure of the vaginal cuff is a critical component of a robotic assisted hysterectomy procedure. Our aim in this study is to develop ...

Robotic laparoendoscopic single-site gynecologic surgery.

Deep learning reconstruction for 1.5 T cervical spine MRI: effect on interobserver agreement in the evaluation of degenerative changes.

OBJECTIVES: To investigate whether deep learning reconstruction (DLR) provides improved cervical spine MR images using a 1.5 T unit in the evaluation ...

Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods.

OBJECTIVES: In this study, we aimed to differentiate normal cervical graphs and graphs of diseases that cause mechanical neck pain by using deep convo...

Image Recognition and Extraction of Students' Human Motion Features Based on Graph Neural Network.

In order to improve students' overall subhealth behavior, teenagers' physical health problems have attracted more and more attention. The state clearl...

Diagnosis of Early Cervical Cancer with a Multimodal Magnetic Resonance Image under the Artificial Intelligence Algorithm.

This research was conducted to explore the value of multimodal magnetic resonance imaging (MRI) based on the alternating direction algorithm in the di...

Deep Learning-Assisted Automated Single Cell Electroporation Platform for Effective Genetic Manipulation of Hard-to-Transfect Cells.

Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms o...

Robot-assisted versus laparoscopic minimally invasive surgery for the treatment of stage I endometrial cancer.

OBJECTIVE: Recent reports in both cervical and endometrial cancer suggest that minimally invasive surgery (MIS) had an unanticipated negative impact o...

Robotic Management of Diaphragmatic Endometriosis in 10 Steps.

OBJECTIVE: To present 10 standardized steps of the surgical management of diaphragmatic endometriosis using Da Vinci robotic assistance.

Scrutinizing high-risk patients from ASC-US cytology via a deep learning model.

BACKGROUND: Atypical squamous cells of undetermined significance (ASC-US) is the most frequent but ambiguous abnormal Papanicolaou (Pap) interpretatio...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accur...

Test Strategy Optimization Based on Soft Sensing and Ensemble Belief Measurement.

Resulting from the short production cycle and rapid design technology development, traditional prognostic and health management (PHM) approaches becom...