Obstetrics & Gynecology

Effect of Deep Learning Reconstruction on Evaluating Cervical Spinal Canal Stenosis With Computed Tomography.

OBJECTIVE: Magnetic resonance imaging (MRI) is commonly used to evaluate cervical spinal canal stenosis; however, some patients are ineligible for MRI. We aimed to assess the effect of deep learning reconstruction (DLR) in evaluating cervical spinal canal stenosis using computed tomography (CT) compared with hybrid iterative reconstruction (hybrid IR).

Measurement of interspinous motion in dynamic cervical radiographs using a deep learning-based segmentation model.

OBJECTIVE: Interspinous motion (ISM) is a representative method for evaluating the functional fusion status following anterior cervical discectomy and fusion (ACDF) surgery, but the associated measuring difficulty and potential errors in the clinical setting remain concerns. The aim of this study was to investigate the feasibility of a deep learning-based segmentation model for measuring ISM in pa...

Caffeinated non-alcoholic beverages on the postpartum mental health related to the COVID-19 pandemic by a cross-sectional study in Argentina.

PURPOSE: This work aimed to study postpartum mental outcomes and determinants of the intake of caffeinated beverages during the pandemic in women from...

Validation of a Salivary miRNA Signature of Endometriosis - Interim Data.

BACKGROUND: The discovery of a saliva-based micro–ribonucleic acid (miRNA) signature for endometriosis in 2022 opened up new perspectives for early an...

Research on the impact of industrial robot application on the status of countries in manufacturing global value chains.

The fast growth in the installation of industrial robots has had a major impact on the comparative advantage of nations and the division of labor in g...

Robotic-assisted gynecologic surgery in an older population: A comparison study.

INTRODUCTION: Robotic-assisted surgery in select patients has been shown to result in less peri-operative morbidity. Few studies have explored the ass...

Biodegradable Magnetic Hydrogel Robot with Multimodal Locomotion for Targeted Cargo Delivery.

Recent strides in the development of untethered miniature robots have shown the advantages of diverse actuation methods, flexible maneuverability, and...

Comparison of surgical outcomes between robot-assisted laparoscopic hysterectomy and conventional total laparoscopic hysterectomy in gynecologic benign disease: a single-center cohort study.

We compared the surgical outcomes of robot-assisted laparoscopic hysterectomy (RAH) and total laparoscopic hysterectomy (TLH). This single-center coho...

Learning curve and factors influencing successful robot-assisted bilateral sentinel lymph node mapping in early-stage cervical cancer: an observational cohort study.

OBJECTIVES: To evaluate whether a learning curve affects the bilateral sentinel lymph node (SLN) detection in early-stage cervical cancer.

Creating an ignorance-base: Exploring known unknowns in the scientific literature.

BACKGROUND: Scientific discovery progresses by exploring new and uncharted territory. More specifically, it advances by a process of transforming unkn...

Delineation of clinical target volume and organs at risk in cervical cancer radiotherapy by deep learning networks.

PURPOSE: Delineation of the clinical target volume (CTV) and organs-at-risk (OARs) is important in cervical cancer radiotherapy. But it is generally l...

Deep learning for segmentation of the cervical cancer gross tumor volume on magnetic resonance imaging for brachytherapy.

BACKGROUND: Segmentation of the Gross Tumor Volume (GTV) is a crucial step in the brachytherapy (BT) treatment planning workflow. Currently, radiation...

Image quality and lesion detectability of deep learning-accelerated T2-weighted Dixon imaging of the cervical spine.

OBJECTIVES: To validate the subjective image quality and lesion detectability of deep learning-accelerated Dixon (DL-Dixon) imaging of the cervical sp...

Prenatal Diagnosis of Placenta Accreta Spectrum Disorders: Deep Learning Radiomics of Pelvic MRI.

BACKGROUND: Diagnostic performance of placenta accreta spectrum (PAS) by prenatal MRI is unsatisfactory. Deep learning radiomics (DLR) has the potenti...

Deep learning-based markerless lung tumor tracking in stereotactic radiotherapy using Siamese networks.

BACKGROUND: Radiotherapy (RT) is involved in about 50% of all cancer patients, making it a very important treatment modality. The most common type of ...

Applications of artificial intelligence in ovarian stimulation: a tool for improving efficiency and outcomes.

Because of the birth of the first baby after in vitro fertilization (IVF), the field of assisted reproductive technologies (ARTs) has seen significant...

Artificial intelligence and assisted reproductive technologies: 2023. Ready for prime time? Or not.

Artificial intelligence has transformed many aspects of health care from image analysis to clinical decision making. Its evolution in medicine has bee...

Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images.

Deep learning technology has been used in the medical field to produce devices for clinical practice. Deep learning methods in cytology offer the pote...

Tafoxiparin, a novel drug candidate for cervical ripening and labor augmentation: results from 2 randomized, placebo-controlled studies.

BACKGROUND: Slow progression of labor is a common obstetrical problem with multiple associated complications. Tafoxiparin is a depolymerized form of h...

Neurosurgical skills analysis by machine learning models: systematic review.

Machine learning (ML) models are being actively used in modern medicine, including neurosurgery. This study aimed to summarize the current application...