Obstetrics & Gynecology

Unleashing the mechanism among environmental regulation, artificial intelligence, and global value chain leaps: a roadmap toward digital revolution and environmental sustainability.

Strengthening environmental regulation and adhering to the green as well as sustainable development of China's manufacturing industry has become an inevitable trend. Technological innovation leads to industrial transformation, and artificial intelligence becomes a new driving force for core competitiveness and value chain upgrading. Is there a link between environmental regulation, artificial inte...

Equation learning to identify nano-engineered particle-cell interactions: an interpretable machine learning approach.

Designing nano-engineered particles capable of the delivery of therapeutic and diagnostic agents to a specific target remains a significant challenge. Understanding how interactions between particles and cells are impacted by the physicochemical properties of the particle will help inform rational design choices. Mathematical and computational techniques allow for details regarding particle-cell i...

Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging.

BACKGROUND: Upon the discovery of ovarian cysts, obstetricians, gynecologists, and ultrasound examiners must address the common clinical challenge of ...

Development of a deep learning method for improving diagnostic accuracy for uterine sarcoma cases.

Uterine sarcomas have very poor prognoses and are sometimes difficult to distinguish from uterine leiomyomas on preoperative examinations. Herein, we ...

Towards machine learning for hydrogel drug delivery systems.

Hydrogel drug delivery system development is complex and laborious, and machine learning (ML) techniques hold great promise in accelerating the proces...

Establishment of a model for predicting the outcome of induced labor in full-term pregnancy based on machine learning algorithm.

To evaluate and establish a prediction model of the outcome of induced labor based on machine learning algorithm. This was a cross-sectional design. T...

Sagittal intervertebral rotational motion: a deep learning-based measurement on flexion-neutral-extension cervical lateral radiographs.

BACKGROUND: The analysis of sagittal intervertebral rotational motion (SIRM) can provide important information for the evaluation of cervical diseases...

A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology.

We introduce a method for training neural networks to perform image or volume segmentation in which prior knowledge about the topology of the segmente...

Deep learning in CT image segmentation of cervical cancer: a systematic review and meta-analysis.

BACKGROUND: This paper attempts to conduct a systematic review and meta-analysis of deep learning (DLs) models for cervical cancer CT image segmentati...

High-content video flow cytometry with digital cell filtering for label-free cell classification by machine learning.

Recent development of imaging flow cytometry (IFC) has enabled the measurements of single cells with high throughput, where fluorescent labels provide...

Exploring risk factors for cervical lymph node metastasis in papillary thyroid microcarcinoma: construction of a novel population-based predictive model.

BACKGROUND: Machine learning was a highly effective tool in model construction. We aim to establish a machine learning-based predictive model for pred...

Volume-outcome relationship in intra-abdominal robotic-assisted surgery: a systematic review.

As robotic-assisted surgery (RAS) expands to smaller centres, platforms are shared between specialities. Healthcare providers must consider case volum...

Artificial intelligence-based algorithm for cervical vertebrae maturation stage assessment.

OBJECTIVE: The aim of this study was to develop an artificial intelligence (AI) algorithm to automatically and accurately determine the stage of cervi...

RU-Net: An improved U-Net placenta segmentation network based on ResNet.

BACKGROUND: In recent years, with the increase of late puerperium, cesarean section and induced abortion, the incidence of placenta accreta has been o...

3Ddose verification in prostate proton therapy with deep learning-based proton-acoustic imaging.

Dose delivery uncertainty is a major concern in proton therapy, adversely affecting the treatment precision and outcome. Recently, a promising techniq...

Analysis of suction-based gripping strategies in wildlife towards future evolutions of the obstetrical suction cup.

The design of obstetrical suction cups used for vacuum assisted delivery has not substantially evolved through history despite of its inherent limitat...

Current understanding of biological interactions and processing of DNA origami nanostructures: Role of machine learning and implications in drug delivery.

DNA origami has emerged as an exciting avenue that provides a versatile two and three-dimensional DNA-based platform for nanomedicine and drug deliver...

Deep-learning-reconstructed high-resolution 3D cervical spine MRI for foraminal stenosis evaluation.

OBJECTIVE: To compare standard-of-care two-dimensional MRI acquisitions of the cervical spine with those from a single three-dimensional MRI acquisiti...

Modular robotic platform for precision neurosurgery with a bio-inspired needle: System overview and first in-vivo deployment.

Over the past 10 years, minimally invasive surgery (MIS) has shown significant benefits compared to conventional surgical techniques, with reduced tra...

Cx22: A new publicly available dataset for deep learning-based segmentation of cervical cytology images.

The segmentation of cervical cytology images plays an important role in the automatic analysis of cervical cytology screening. Although deep learning-...