Obstetrics & Gynecology

[The study of implementation of digital technologies on sphere of labor protection and its impact on personnel of enterprises of marine industry].

The innovative technologies are becoming widespread in all spheres of human life, including labor protection. The AI, modern systems of monitoring and data analysis permit to develop devices with functions to determine physical conditions of workers, to track and to prevent emergency situations and to minimize occupational traumatism. The mentioned advantages of such devices are very important in ...

Modification of the toronto rehabilitation institute-hand function test for integration into robot-assisted therapy: technical validation and usability.

BACKGROUND: Effective rehabilitation of the upper extremity function is vital for individuals recovering from stroke or cervical spinal cord injury, as it can enable them to regain independence in daily tasks. While robotic therapy provides precise and consistent motor training, it often lacks the integration of real-world objects that stimulate sensorimotor experiences. The Toronto Rehabilitation...

Enhancing Obstetric Decision-Making With AI: A Systematic Review of AI Models for Predicting Mode of Delivery.

Accurate prediction of the mode of delivery is critical for optimizing maternal and neonatal outcomes and reducing unnecessary cesarean sections. In r...

Advanced holographic convolutional dense networks and Tangent runner optimization for enhanced polycystic ovarian disease classification.

Polycystic Ovarian Disease (PCOD) is among the most prevalent endocrine disorders complicating the health of innumerable women worldwide due to lack o...

Artificial intelligence guided imaging as a tool to fill gaps in health care delivery.

Deep vein thrombosis (DVT) causes significant morbidity/mortality and timely diagnosis often via ultrasound is critical. However, the shortage of trai...

Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence.

PURPOSE: Endometrial cancer (EC) is the most common gynecologic cancer in the United States with rising incidence and mortality. Despite optimal treat...

Leveraging AI to explore structural contexts of post-translational modifications in drug binding.

Post-translational modifications (PTMs) play a crucial role in allowing cells to expand the functionality of their proteins and adaptively regulate th...

Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births.

OBJECTIVE: This study aimed to develop a machine learning (ML) model integrated with SHapley Additive exPlanations (SHAP) analysis to predict postpart...

Utilizing explainable machine learning for progression-free survival prediction in high-grade serous ovarian cancer: insights from a prospective cohort study.

BACKGROUND: High-grade serous ovarian cancer (HGSOC) remains one of the most challenging gynecological malignancies, with over 70% of ovarian cancer p...

Deep Learning Model of Primary Tumor and Metastatic Cervical Lymph Nodes From CT for Outcome Predictions in Oropharyngeal Cancer.

IMPORTANCE: Primary tumor (PT) and metastatic cervical lymph node (LN) characteristics are highly associated with oropharyngeal squamous cell carcinom...

Advancement in early diagnosis of polycystic ovary syndrome: biomarker-driven innovative diagnostic sensor.

Polycystic ovary syndrome (PCOS) is a heterogeneous multifactorial endocrine disorder that affects one in five women around the globe. The pathology s...

Performance of radiomics analysis in ultrasound imaging for differentiating benign from malignant adnexal masses: A systematic review and meta-analysis.

INTRODUCTION: We present the state of the art of ultrasound-based machine learning (ML) radiomics models in the context of ovarian masses and analyze ...

Artificial Intelligence (AI) and The Journal of Pediatric and Adolescent Gynecology (JPAG).

Ovarian Cancer Detection in Ascites Cytology with Weakly Supervised Model on Nationwide Data Set.

Conventional ascitic fluid cytology for detecting ovarian cancer is limited by its low sensitivity. To address this issue, this multicenter study deve...

Statistical algorithms for the analysis of deleterious genetic mutations.

We present algorithms for model selection and parameter estimation concerning deleterious genetic mutations. Three models are considered: single gene ...

Standardizing a microbiome pipeline for body fluid identification from complex crime scene stains.

Recent advances in next-generation sequencing have opened up new possibilities for applying the human microbiome in various fields, including forensic...

Evaluation of deliverable artificial intelligence-based automated volumetric arc radiation therapy planning for whole pelvic radiation in gynecologic cancer.

This study aimed to develop a deep learning (DL)-based deliverable whole pelvic volumetric arc radiation therapy (VMAT) for patients with gynecologic ...

Advancements in fluorescent nanobiosensors for HPV detection: from integrating nanomaterials to DNA nanotechnology.

Human papillomavirus (HPV) is a leading cause of cervical cancer and other malignancies, necessitating the development of highly sensitive and specifi...

Hybrid Neural network and machine learning models with improved optimization method for gut microbiome effects on the sleep quality in patients with endometriosis.

BACKGROUND AND OBJECTIVE: Endometriosis is a chronic gynecological condition known to affect the quality of life of millions of women globally, often ...

Peritoneal cytology predicting distant metastasis in uterine carcinosarcoma: machine learning model development and validation.

OBJECTIVE: This study develops and validates a machine learning model using peritoneal cytology to predict distant metastasis in uterine carcinosarcom...