Obstetrics & Gynecology

IDT: An incremental deep tree framework for biological image classification.

Nowadays, breast and cervical cancers are respectively the first and fourth most common causes of cancer death in females. It is believed that, automated systems based on artificial intelligence would allow the early diagnostic which increases significantly the chances of proper treatment and survival. Although Convolutional Neural Networks (CNNs) have achieved human-level performance in object cl...

Deep learning-based histotype diagnosis of ovarian carcinoma whole-slide pathology images.

Ovarian carcinoma has the highest mortality of all female reproductive cancers and current treatment has become histotype-specific. Pathologists diagnose five common histotypes by microscopic examination, however, histotype determination is not straightforward, with only moderate interobserver agreement between general pathologists (Cohen's kappa 0.54-0.67). We hypothesized that machine learning (...

Development and validation of a machine-learning algorithm to predict the relevance of scientific articles within the field of teratology.

The Dutch Teratology Information Service Lareb counsels healthcare professionals and patients about medication use during pregnancy and lactation. To ...

A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy.

PURPOSE: Fast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rat...

The analgesic efficacy of ultrasound-guided transversus abdominis plane block vs. local anesthetic infiltration technique in major gynecologic surgery: A randomized controlled trial.

BACKGROUND AND AIM: Transversus abdominis plane (TAP) block and local anesthetic infiltration (LAI) technique are used as part of the multimodal analg...

Answer to the letter to the editor by Zhi-Hui Dai concerning "Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion" by Rudisill SS et al. (Eur Spine J [2022]; doi: 10.1007/s00586-022-07238-3).

Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy.

BACKGROUND: Accurate diagnosis of unexplained cervical lymphadenopathy (CLA) using medical images heavily relies on the experience of radiologists, wh...

Creating Sustainable Cultural Industries: The Perspective of Artificial Intelligence and Global Value Chain.

In the era of artificial intelligence (AI), cultural industries have introduced new development opportunities, and their global value chain (GVC) posi...

Letter to the Editor concerning "Artificial intelligence in predicting early-onset adjacent segment degeneration following anterior cervical discectomy and fusion" by Rudisill SS, et al. (Eur Spine J [2022]; doi: 10.1007/s00586-022-07238-3).

Robot-assisted Laparoscopic Bilateral Ileal Ureter in Duplex Ureter With Strictures After Treatment Failure of Allium Stents.

BACKGROUND: Ureteral injury and vaginal fistula are common complications after surgical treatment and radiotherapy of gynecological tumor. Ureteral in...

Initial experience of a deep learning application for the differentiation of Kikuchi-Fujimoto's disease from tuberculous lymphadenitis on neck CECT.

Neck contrast-enhanced CT (CECT) is a routine tool used to evaluate patients with cervical lymphadenopathy. This study aimed to evaluate the ability o...

Evaluation of Spatial Attentive Deep Learning for Automatic Placental Segmentation on Longitudinal MRI.

BACKGROUND: Automated segmentation of the placenta by MRI in early pregnancy may help predict normal and aberrant placenta function, which could impro...

On-demand anchoring of wireless soft miniature robots on soft surfaces.

Untethered soft miniature robots capable of accessing hard-to-reach regions can enable new, disruptive, and minimally invasive medical procedures. How...

Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.

Deep learning (DL) based approach aims to construct a full workflow solution for cervical cancer with external beam radiation therapy (EBRT) and brach...

iCVM: An Interpretable Deep Learning Model for CVM Assessment Under Label Uncertainty.

The Cervical Vertebral Maturation (CVM) method aims to determine the craniofacial skeletal maturational stage, which is crucial for orthodontic and or...

How are Patients Describing You Online? A Natural Language Processing Driven Sentiment Analysis of Online Reviews on CSRS Surgeons.

STUDY DESIGN: A quantitative analysis of written, online reviews of Cervical Spine Research Society (CSRS) surgeons.

The Artificial Intelligence System for the Generation of Sports Education Guidance Model and Physical Fitness Evaluation Under Deep Learning.

In recent years, China's achievements in artificial intelligence (AI) have attracted the attention of the world, and AI technology has penetrated into...

Deep learning reconstruction for the evaluation of neuroforaminal stenosis using 1.5T cervical spine MRI: comparison with 3T MRI without deep learning reconstruction.

PURPOSE: To compare image quality and interobserver agreement in evaluations of neuroforaminal stenosis between 1.5T cervical spine magnetic resonance...

Predicting the Next-Day Perceived and Physiological Stress of Pregnant Women by Using Machine Learning and Explainability: Algorithm Development and Validation.

BACKGROUND: Cognitive behavioral therapy-based interventions are effective in reducing prenatal stress, which can have severe adverse health effects o...

Application of the sliding window method and Mask-RCNN method to nuclear recognition in oral cytology.

BACKGROUND: We aimed to develop an artificial intelligence (AI)-assisted oral cytology method, similar to cervical cytology. We focused on the detecti...