Obstetrics & Gynecology

Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning.

The hyoid bone displacement and rotation are critical kinematic events of the swallowing process in the assessment of videofluoroscopic swallow studies (VFSS). However, the quantitative analysis of such events requires frame-by-frame manual annotation, which is labor-intensive and time-consuming. Our work aims to develop a method of automatically tracking hyoid bone displacement and rotation in VF...

Tracking and navigation of a microswarm under laser speckle contrast imaging for targeted delivery.

Micro/nanorobotic swarms consisting of numerous tiny building blocks show great potential in biomedical applications because of their collective active delivery ability, enhanced imaging contrast, and environment-adaptive capability. However, in vivo real-time imaging and tracking of micro/nanorobotic swarms remain a challenge, considering the limited imaging size and spatial-temporal resolution o...

An integrated machine learning-based model for joint diagnosis of ovarian cancer with multiple test indicators.

OBJECTIVE: To construct a machine learning diagnostic model integrating feature dimensionality reduction techniques and artificial neural network clas...

A Histopathologic Image Analysis for the Classification of Endocervical Adenocarcinoma Silva Patterns Depend on Weakly Supervised Deep Learning.

Twenty-five percent of cervical cancers are classified as endocervical adenocarcinomas (EACs), which comprise a highly heterogeneous group of tumors. ...

Prediction of pregnancy-related complications in women undergoing assisted reproduction, using machine learning methods.

OBJECTIVE: To use machine learning methods to develop prediction models of pregnancy complications in women who conceived with assisted reproductive t...

Review of robotic surgery platforms and end effectors.

In the last 50 years, the number of companies producing automated devices for surgical operations has grown extensively. The population started to be ...

Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rate.

RESEARCH QUESTION: Could EMBRYOLY, an artificial intelligence embryo evaluation tool, assist embryologists to increase first cycle pregnancy rate and ...

Classification of inertial sensor-based gait patterns of orthopaedic conditions using machine learning: A pilot study.

Elderly patients often have more than one disease that affects walking behavior. An objective tool to identify which disease is the main cause of func...

Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity.

BACKGROUND: Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity. Precision approach ...

Paeonol impacts ovarian cancer cell proliferation, migration, invasion and apoptosis via modulating the transforming growth factor beta/smad3 signaling pathway.

Paeonol (2-hydroxy-4-methoxyphenylacetophenone) is a natural phenolic component isolated from the root bark of peony with multiple pharmacological act...

Robot-assisted transcervical esophagectomy with a bilateral cervical approach for thoracic esophagectomy.

BACKGROUND: Thoracic esophageal cancer resection through the neck approach has recently been reported as mediastinoscopic surgery. We present the firs...

Interactive segmentation of medical images using deep learning.

Medical image segmentation algorithms based on deep learning have achieved good segmentation results in recent years, but they require a large amount ...

Large Language Models and Healthcare Alliance: Potential and Challenges of Two Representative Use Cases.

Large language models (LLMS) emerge as the most promising Natural Language Processing approach for clinical practice acceleration (i.e., diagnosis, pr...

Validation of a Simulation Model for Robotic Myomectomy.

STUDY OBJECTIVE: Several simulation models have been evaluated for gynecologic procedures such as hysterectomy, but there are limited published data f...

Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.

Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments ...

A quantitative evaluation of the deep learning model of segmentation and measurement of cervical spine MRI in healthy adults.

PURPOSE: To evaluate the 3D U-Net model for automatic segmentation and measurement of cervical spine structures using magnetic resonance (MR) images o...

Efficacy of stereotactic body radiotherapy and response prediction using artificial intelligence in oligometastatic gynaecologic cancer.

PURPOSE: We present a large real-world multicentric dataset of ovarian, uterine and cervical oligometastatic lesions treated with SBRT exploring effic...

Dynamics of labor and capital in AI vs. non-AI industries: A two-industry model analysis.

There is an imbalance in the development of artificial intelligence between industries. Compared to non-AI enterprise, AI- enterprise will save labor,...

Exploring a novel seven-gene marker and mitochondrial gene TMEM38A for predicting cervical cancer radiotherapy sensitivity using machine learning algorithms.

BACKGROUND: Radiotherapy plays a crucial role in the management of Cervical cancer (CC), as the development of resistance by cancer cells to radiother...

Machine learning to predict unintended pregnancy among reproductive-age women in Ethiopia: evidence from EDHS 2016.

BACKGROUND: An unintended pregnancy is a pregnancy that is either unwanted or mistimed, such as when it occurs earlier than desired. It is one of the ...