Obstetrics & Gynecology

Developing an interpretation model for body fluid identification.

Criminal investigations, particularly sexual assaults, frequently require the identification of body...

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...

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 clinica...

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 t...

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 implicat...

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 patien...

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...

Artificial intelligence in obstetric anaesthesia: an unlikely player?

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 p...

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 fo...

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 thrombos...

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 ...

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 ...

Deep neural network (DNN) modelling for prediction of the mode of delivery.

One of the factors that worry obstetricians the most is the method of delivery. In recent years, the...

Development and validation of an ultrasound-based deep learning radiomics nomogram for predicting the malignant risk of ovarian tumours.

BACKGROUND: The timely identification and management of ovarian cancer are critical determinants of ...

Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.

The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for imp...

The Evolving Landscape of Cervical Cancer: Breakthroughs in Screening and Therapy Through Integrating Biotechnology and Artificial Intelligence.

Cervical cancer (CC) continues to be a major worldwide health concern, profoundly impacting the live...

Deep learning-based computer-aided diagnosis system for the automatic detection and classification of lateral cervical lymph nodes on original ultrasound images of papillary thyroid carcinoma: a prospective diagnostic study.

PURPOSE: This study aims to develop a deep learning-based computer-aided diagnosis (CAD) system for ...

The association between PM components and blood pressure changes in late pregnancy: A combined analysis of traditional and machine learning models.

BACKGROUND: PM is a harmful mixture of various chemical components that pose a challenge in determin...