Obstetrics & Gynecology

Ready for the robot? A cross-sectional survey of OB/GYN fellowship directors' experience and expectations of their incoming fellow's robotic surgical skills.

To describe OB/GYN fellowship directors' (FDs) observations, expectations, and preferences of incoming fellow's robotic surgery preparedness. Cross-sectional study. OB/GYN FDs in gynecologic oncology, minimally invasive gynecologic surgery, female pelvic medicine and reconstructive surgery, and reproductive endocrinology and infertility in the United States. 60 FDs answered the questionnaire. Part...

Predicting vaginal birth after previous cesarean: Using machine-learning models and a population-based cohort in Sweden.

INTRODUCTION: Predicting a woman's probability of vaginal birth after cesarean could facilitate the antenatal decision-making process. Having a previous vaginal birth strongly predicts vaginal birth after cesarean. Delivery outcome in women with only a cesarean delivery is more unpredictable. Therefore, to better predict vaginal birth in women with only one prior cesarean delivery and no vaginal d...

Role of Red Cell Indices in Screening for Beta Thalassemia Trait: an Assessment of the Individual Indices and Application of Machine Learning Algorithm.

Antenatal screening for beta thalassemia trait (BTT) followed by counseling of couples is an efficient way of thalassemia control. Since high performa...

Style transfer strategy for developing a generalizable deep learning application in digital pathology.

BACKGROUND AND OBJECTIVES: Despite recent advances in artificial intelligence for medical images, the development of a robust deep learning model for ...

Prediction of obstetrical and fetal complications using automated electronic health record data.

An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that coul...

Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic.

INTRODUCTION: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease...

Evaluation of a convolutional neural network for ovarian tumor differentiation based on magnetic resonance imaging.

OBJECTIVES: There currently lacks a noninvasive and accurate method to distinguish benign and malignant ovarian lesion prior to treatment. This study ...

Discovery of gene module acting on ubiquitin-mediated proteolysis pathway by co-expression network analysis for endometriosis.

RESEARCH QUESTION: Is abnormal gene module expression in the eutopic endometrium related to the occurrence of endometriosis?

Natural language processing with machine learning to predict outcomes after ovarian cancer surgery.

OBJECTIVE: To determine if natural language processing (NLP) with machine learning of unstructured full text documents (a preoperative CT scan) improv...

Fertility preservation before hematopoetic stem cell transplantation: a case series of women with GATA binding protein 2 deficiency, dedicator of cytokinesis 8 deficiency, and sickle cell disease.

OBJECTIVE: To describe fertility characteristics, outcomes of oocyte cryopreservation cycles, and safety of ovarian stimulation in patients with GATA ...

Development and validation of a deep learning algorithm for auto-delineation of clinical target volume and organs at risk in cervical cancer radiotherapy.

PURPOSE: The delineation of the clinical target volume (CTV) is a crucial, laborious and subjective step in cervical cancer radiotherapy. The aim of t...

Clinical predictive modelling of post-surgical recovery in individuals with cervical radiculopathy: a machine learning approach.

Prognostic models play an important role in the clinical management of cervical radiculopathy (CR). No study has compared the performance of modern ma...

The impact of surgical learning curve on survival - reopening the door for minimally invasive surgery in the management of cervical cancer?

Artificial intelligence in in vitro fertilization: a computer decision support system for day-to-day management of ovarian stimulation during in vitro fertilization.

OBJECTIVE: To describe a computer algorithm designed for in vitro fertilization (IVF) management and to assess the algorithm's accuracy in the day-to-...

Temporal Trends in Cervical Spine Curvature of South Korean Adults Assessed by Deep Learning System Segmentation, 2006-2018.

IMPORTANCE: The loss of the physiologic cervical lordotic curve is a common degenerative disorder known to be associated with abnormal spinal alignmen...

Human-machine alliance against cervical cancer.

Predicting complete cytoreduction for advanced ovarian cancer patients using nearest-neighbor models.

BACKGROUND: The foundation of modern ovarian cancer care is cytoreductive surgery to remove all macroscopic disease (R0). Identification of R0 resecti...

Integration of AI and Machine Learning in Radiotherapy QA.

The use of machine learning and other sophisticated models to aid in prediction and decision making has become widely popular across a breadth of disc...

REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.

BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as varian...

Transoral robotic parapharyngeal approach to the submandibular space.

The aim of the study was to demonstrate a novel transoral parapharyngeal approach to the submandibular space. The method used was the clinical case of...