Obstetrics & Gynecology

Objective and Subjective Assessment of Bladder Function after Robot-assisted Laparoscopic Radical Hysterectomy for Early-stage Cervical Cancer.

STUDY OBJECTIVE: To examine whether objective bladder function after robot-assisted radical hysterectomy (RRH) for early-stage cervical cancer is correlated with subjective patient-reported outcomes and quality of life during the first year after RRH.

Performance Evaluation of Machine Learning Algorithm for Classification of Unintended Pregnancy among Married Women in Bangladesh.

Intended pregnancy is one of the significant indicators of women's well-being. Globally, 74 million women become pregnant every year without planning. Unintended pregnancies account for 28% of all pregnancies among married women in Bangladesh. This study aimed to investigate the performance of six different machine learning (ML) algorithms applied to predict unintended pregnancies among married wo...

Short report: surgery for implantable brain-computer interface assisted by robotic navigation system.

We present an implantable brain-computer interface surgical case assisted by robotic navigation system in an elderly patient with tetraplegia caused b...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior...

Deep learning-based multimodal image analysis for cervical cancer detection.

Cervical cancer is the fourth most common cancer in women, and its precise detection plays a critical role in disease treatment and prognosis predicti...

Deep Learning Enabled Neck Motion Detection Using a Triboelectric Nanogenerator.

The state of neck motion reflects cervical health. To detect the motion state of the human neck is of important significance to healthcare intelligenc...

Formulation design and optimization of cationic-charged liposomes of brimonidine tartrate for effective ocular drug delivery by design of experiment (DoE) approach.

OBJECTIVE: The present study was aimed to design and optimize brimonidine tartrate (BRT) loaded cationic-charged liposome formulation with enhanced tr...

Combining multiparametric MRI features-based transfer learning and clinical parameters: application of machine learning for the differentiation of uterine sarcomas from atypical leiomyomas.

OBJECTIVES: To explore the feasibility and effectiveness of machine learning (ML) based on multiparametric magnetic resonance imaging (mp-MRI) feature...

Application of Convolutional Neural Network (CNN) to Recognize Ship Structures.

The purpose of this paper is to study the recognition of ships and their structures to improve the safety of drone operations engaged in shore-to-ship...

Deep learning combined with radiomics for the classification of enlarged cervical lymph nodes.

PURPOSE: To investigate the application of deep learning combined with traditional radiomics methods for classifying enlarged cervical lymph nodes.

Application of artificial intelligence in the diagnosis and prognostic prediction of ovarian cancer.

In recent years, the wide application of artificial intelligence (AI) has dramatically improved the work efficiency of clinicians and reduced their wo...

A large intrathoracic goiter with tracheal stenosis: Complete resection using a robot-assisted thoracoscopic approach.

Growing intrathoracic goiters may compress surrounding organs and deteriorate the cardiopulmonary function. Treating such cases requires carefully con...

A machine learning approach applied to gynecological ultrasound to predict progression-free survival in ovarian cancer patients.

In a growing number of social and clinical scenarios, machine learning (ML) is emerging as a promising tool for implementing complex multi-parametric ...

RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model.

Cervical cancer is one of the main causes of death from cancer in women. However, it can be treated successfully at an early stage. This study aims to...

Multi-input adaptive neural network for automatic detection of cervical vertebral landmarks on X-rays.

Cervical vertebral landmark detection is a significant pre-task for vertebral relative motion parameter measurement, which is helpful for doctors to d...

Deep learning-based plane pose regression in obstetric ultrasound.

PURPOSE: In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimension...

Using DeepLab v3 + -based semantic segmentation to evaluate platelet activation.

This research used DeepLab v3 + -based semantic segmentation to automatically evaluate the platelet activation process and count the number of platele...

Improved diagnostic performance of plain radiography for cervical ossification of the posterior longitudinal ligament using deep learning.

BACKGROUND: A high false-negative rate has been reported for the diagnosis of ossification of the posterior longitudinal ligament (OPLL) using plain r...

Predicting exclusive breastfeeding in maternity wards using machine learning techniques.

BACKGROUND AND OBJECTIVE: Adequate support in maternity wards is decisive for breastfeeding outcomes during the first year of life. Quality improvemen...

Hybrid Loss-Constrained Lightweight Convolutional Neural Networks for Cervical Cell Classification.

Artificial intelligence (AI) technologies have resulted in remarkable achievements and conferred massive benefits to computer-aided systems in medical...