Obstetrics & Gynecology

Emerging landscape of bioinformatics and artificial intelligence applications in cell-penetrating peptide-based delivery.

INTRODUCTION: Peptides play diverse roles in biological processes, including drug discovery, antibacterial activity, and protein-protein interactions, making peptide prediction a crucial field. The development of bioinformatics tools has significantly enhanced our ability to study and harness peptide potential. Among these, cell-penetrating peptides (CPP) are a unique class of polypeptides capable...

Preoperative prediction of cervical cancer recurrence using explainable MRI radiomics: a SHAP-Guided machine learning study.

PURPOSE: To develop and validate a machine learning model that integrated MRI radiomics features and clinical factors for preoperative prediction of postoperative recurrence in cervical cancer. METHODS: This retrospective study included 268 patients with pathologically confirmed cervical cancer (training cohort: n = 185; validation cohort: n = 83). A total of 124 radiomics features were extracted ...

Evaluating Retrieval-Augmented Large Language Models on External Cervical Resorption: A Comparative Study of Gemini and NotebookLM.

INTRODUCTION: This study evaluated the accuracy and consistency of two large language models developed by Alphabet Inc., Google Gemini (GG), a base co...

Performance Assessment of a Deep Learning-based Algorithm for Ovarian Cancer Histotyping in an Independent Data Set.

Artificial intelligence diagnostic tools show promise for improving histotype classification in epithelial ovarian cancer but face challenges due to s...

A multi-task deep learning framework for intraoperative diagnosis of thyroid cancer metastasis using whole slide images.

BACKGROUND: Lymph node metastasis (LNM) is a critical prognostic indicator in papillary thyroid carcinoma (PTC), significantly influencing surgical de...

Advanced artificial intelligence combined with SERS platforms for diagnosis and therapeutic effects of cancer in clinical applications.

Surface-Enhanced Raman Spectroscopy (SERS) has become a valuable way to detect small amounts of molecules due to its high sensitivity. Nonetheless, ap...

An interactive and explainable AI approach to improve human-machine teaming in cancer subtyping from digital cytopathology.

Algorithmic decision support is rapidly becoming a staple of personalized medicine, particularly for high-stakes recommendations such as cancer subtyp...

Fetal cardiac remodeling in second trimester in pregnancies with pre-eclampsia and/or fetal growth restriction: deep-learning-based approach using population-wide data.

OBJECTIVE: Pre-eclampsia (PE) and fetal growth restriction (FGR) have been shown to impact fetal cardiac remodeling in the third trimester and postnat...

Artificial intelligence in obstetrics and gynecology: Evaluating ChatGPT and Google Gemini in answering patient questions.

INTRODUCTION: To evaluate the accuracy and completeness of responses across common obstetrical and gynecologic topics generated by the large language ...

Cervical cancer in the modern era: cutting-edge strategies for diagnosis and treatment.

Cervical cancer remains a major cause of mortality among women worldwide, highlighting the need for advances in diagnostic and therapeutic strategies....

Machine learning-based prediction of postpartum hemorrhage using maternal clinical and biochemical features.

OBJECTIVE: This study evaluates the predictive performance of various machine learning (ML) algorithms for postpartum hemorrhage (PPH), peripartum hys...

Automatic Follicle Counting From Ultrasound Images of Ovaries Using MARDSE-UNET Model.

Detecting ovarian structures in ultrasound images is essential in gynecological and reproductive medicine. An automated detection system can serve as ...

Artificial intelligence-driven precision treatment of reproductive medicine-related diseases: the optimal protocol choice for IVF-ET.

INTRODUCTION: Optimal ovarian stimulation (OS) selection is critical for IVF success, but expert-based decisions often lack consistency in outcomes, c...

Investigating the potential of combining Raman spectroscopy and machine learning for gestational age classification in rat cervical tissue.

Spontaneous preterm birth (SPB) is a leading cause of neonatal morbidity and mortality worldwide. It occurs when the uterine cervix (UC) opens prematu...

A Window Into Vulnerability and Support: At-Risk Mothers' Perinatal Experiences and Perspectives on mHealth-Based Care.

AIM: To examine the perinatal experiences of at-risk mothers and their engagement with mobile-health-based care. DESIGN: A qualitative descriptive stu...

Deep learning enhanced label-free cervical screening via stimulated Raman cytology.

Cervical cancer screening remains pivotal for early detection and effective disease management, yet conventional cytopathological methods relying on s...

The effect of autonomous mobile robots on improving endoscope reprocessing efficiency: a prospective comparative trial (with video).

BACKGROUND AND AIMS: Autonomous mobile robots (AMRs) have an increasingly wide range of medical applications. However, their use in endoscopy centers ...

Ovarian cancer detection from mutual information-ranked clinical biomarkers using an explainable attention-based residual multilayer perceptron.

Ovarian cancer is a major health concern for women, contributing to substantial mortality and morbidity. Timely identification of ovarian cancer is cr...

Japanese Radiology 2025 Updates.

This review provides a comprehensive overview of recent transformative advancements in diagnostic imaging that position Japan at the forefront of radi...

Cervical cancer diagnostics: non-coding RNAs and biosensors to AI-derived methods.

Cervical cancer ranks fourth in terms of cancer mortality among women. The most important risk factor for cervical cancer is infection with HPV 16 and...