Obstetrics & Gynecology

An improved approach for automated cervical cell segmentation with PointRend.

Regular screening for cervical cancer is one of the best tools to reduce cancer incidence. Automated...

Machine learning predicts the serum PFOA and PFOS levels in pregnant women: Enhancement of fatty acid status on model performance.

Human exposure to per- and polyfluoroalkyl substances (PFASs) has received considerable attention, p...

A pilot randomized trial of automatic, artificial intelligence-based vs manual, electronic medical record-based remote postpartum blood pressure monitoring.

Diagnosis of placenta accreta spectrum using ultrasound texture feature fusion and machine learning.

INTRODUCTION: Placenta accreta spectrum (PAS) is an obstetric disorder arising from the abnormal adh...

Deep Learning for Grading Endometrial Cancer.

Endometrial cancer is the fourth most common cancer in women in the United States, with a lifetime r...

Harnessing Disparities in Magnetic Microswarms: From Construction to Collaborative Tasks.

Individual differences in size, experience, and task specialization in natural swarms often result i...

A high-quality dataset featuring classified and annotated cervical spine X-ray atlas.

Recent research in computational imaging largely focuses on developing machine learning (ML) techniq...

Cutting-edge care: unleashing artificial intelligence's potential in gynecologic surgery.

PURPOSE OF REVIEW: Artificial intelligence (AI) is now integrated in our daily life. It has also bee...

Bridging the Diagnostic Gap between Histopathologic and Hysteroscopic Chronic Endometritis with Deep Learning Models.

Chronic endometritis (CE) is an inflammatory pathologic condition of the uterine mucosa characterize...

Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods.

BACKGROUND: Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to anal...

Nose-to-Brain Drug Delivery and Physico-Chemical Properties of Nanosystems: Analysis and Correlation Studies of Data from Scientific Literature.

BACKGROUND: In the last few decades, nose-to-brain delivery has been investigated as an alternative ...

Potential inhibitors of VEGFR1, VEGFR2, and VEGFR3 developed through Deep Learning for the treatment of Cervical Cancer.

Cervical cancer stands as a prevalent gynaecologic malignancy affecting women globally, often linked...

FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches.

Pregnant females may use medications to manage health problems that develop during pregnancy or that...

Advances in artificial intelligence for drug delivery and development: A comprehensive review.

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, ...

Multi-machine Learning Model Based on Habitat Subregions for Outcome Prediction in Adenomyosis Treated by Uterine Artery Embolization.

RATIONALE AND OBJECTIVES: To establish and validate a predictive multi-machine learning model for th...

An Integrated Smart Pond Water Quality Monitoring and Fish Farming Recommendation Aquabot System.

The integration of cutting-edge technologies such as the Internet of Things (IoT), robotics, and mac...

SCAC: A Semi-Supervised Learning Approach for Cervical Abnormal Cell Detection.

Cervical abnormal cell detection plays a crucial role in the early screening of cervical cancer. In ...

Continuous wavelet transform and integration of discrete wavelet transform with principal component analysis and fuzzy inference system for the simultaneous determination of ethinyl estradiol and drospirenone in combined oral contraceptives.

In this study, the spectrophotometric method integrated with continuous wavelet transform (CWT) and ...

Empowering gynaecologists with Artificial Intelligence: Tailoring surgical solutions for fibroids.

BACKGROUND: In recent years, the integration ofArtificial intelligence (AI) into various fields of m...

Identifying miRNA as biomarker for breast cancer subtyping using association rule.

- This paper presents a comprehensive study focused on breast cancer subtyping, utilizing a multifac...

Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.

PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting ...