Obstetrics & Gynecology

Experience of Using Neural Networks to Assess Age-Related Changes in Some Structures of the Skull and Cervical Vertebrae Based on CT Scans (Pilot Project).

UNLABELLED: is to study the possibility of using artificial intelligence technologies for age prediction based on CT studies of some structures of the skull and cervical vertebrae.

Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML) model for first-trimester screening for pre-eclampsia in a large Asian population.

Super-resolution Deep Learning Reconstruction Cervical Spine 1.5T MRI: Improved Interobserver Agreement in Evaluations of Neuroforaminal Stenosis Compared to Conventional Deep Learning Reconstruction.

The aim of this study was to investigate whether super-resolution deep learning reconstruction (SR-DLR) is superior to conventional deep learning reco...

Cervical wear pathobiology by robot-simulated 3-year toothbrushing - New methodological approach.

OBJECTIVES: An ex-vivo study was aimed at (i) programming clinically validated robot three-year random toothbrushing, (ii) evaluating cervical macro- ...

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

OBJECTIVE:  To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Google Bard, and Chatsonic) in generating accurate re...

Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to pro...

Use of natural language processing to uncover racial bias in obstetrical documentation.

Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinical documentation to be integrated in ways that faci...

Construction of deep learning-based convolutional neural network model for automatic detection of fluid hysteroscopic endometrial micropolyps in infertile women with chronic endometritis.

OBJECTIVE(S): Chronic endometritis (CE) is a localized mucosal inflammatory disorder associated with female infertility of unknown etiology, endometri...

Predicting treatment plan approval probability for high-dose-rate brachytherapy of cervical cancer using adversarial deep learning.

Predicting the probability of having the plan approved by the physician is important for automatic treatment planning. Driven by the mathematical foun...

Exploring the potential of machine learning in gynecological care: a review.

Gynecological health remains a critical aspect of women's overall well-being, with profound implications for maternal and reproductive outcomes. This ...

Early identification of postpartum depression using machine learning.

Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.

BACKGROUND: Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor preci...

Predicting cancer-specific survival in Asian/Pacific Islander patients with ovarian clear-cell carcinoma: A novel nomogram developed using machine learning.

Does the presence of abdominal wall adhesions make gynecologic robotic surgery difficult?

This study aimed to assess the status of abdominal wall adhesions resulting from prior surgeries and their impact on the outcomes of robotic surgery. ...

Artificial intelligence in obstetric anaesthesia: an unlikely player?

Clinical feasibility of deep learning-based synthetic CT images from T2-weighted MR images for cervical cancer patients compared to MRCAT.

This work aims to investigate the clinical feasibility of deep learning-based synthetic CT images for cervix cancer, comparing them to MR for calculat...

Cervical lymph node metastasis prediction from papillary thyroid carcinoma US videos: a prospective multicenter study.

BACKGROUND: Prediction of lymph node metastasis (LNM) is critical for individualized management of papillary thyroid carcinoma (PTC) patients to avoid...

Machine Learning as a Diagnostic and Prognostic Tool for Predicting Thrombosis in Cancer Patients: A Systematic Review.

Khorana score (KS) is an established risk assessment model for predicting cancer-associated thrombosis. However, it ignores several risk factors and h...

Fuzzy machine learning logic utilization on hormonal imbalance dataset.

In this research work, a novel fuzzy data transformation technique has been proposed and applied to the hormonal imbalance dataset. Hormonal imbalance...

Application of one-dimensional hierarchical network assisted screening for cervical cancer based on Raman spectroscopy combined with attention mechanism.

Cervical cancer is one of the most common malignant tumors among women, and its pathological change is a relatively slow process. If it can be detecte...