Obstetrics & Gynecology

A Deep Learning Pipeline Using Prior Knowledge for Automatic Evaluation of Placenta Accreta Spectrum Disorders With MRI.

BACKGROUND: The diagnosis of prenatal placenta accreta spectrum (PAS) with magnetic resonance imaging (MRI) is highly dependent on radiologists' experience. A deep learning (DL) method using the prior knowledge that PAS-related signs are generally found along the utero-placental borderline (UPB) may help radiologists, especially those with less experience, to mitigate this issue.

Artificial intelligence-based prediction of cervical lymph node metastasis in papillary thyroid cancer with CT.

OBJECTIVES: To develop an artificial intelligence (AI) system for predicting cervical lymph node metastasis (CLNM) preoperatively in patients with papillary thyroid cancer (PTC) based on CT images.

Clinical application of spinal robot in cervical spine surgery: safety and accuracy of posterior pedicle screw placement in comparison with conventional freehand methods.

The novel robot-assisted (RA) technique has been utilized increasingly to improve the accuracy of cervical pedicle screw placement. Although the clini...

Predicting preterm births from electrohysterogram recordings via deep learning.

About one in ten babies is born preterm, i.e., before completing 37 weeks of gestation, which can result in permanent neurologic deficit and is a lead...

Associating Peritoneal Metastasis With T2-Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study.

BACKGROUND: The preoperative diagnosis of peritoneal metastasis (PM) in epithelial ovarian cancer (EOC) is challenging and can impact clinical decisio...

Real-Time Automatic Assisted Detection of Uterine Fibroid in Ultrasound Images Using a Deep Learning Detector.

OBJECTIVE: Uterine smooth muscle hyperplasia causes a tumor called a uterine fibroid. With an incidence of up to 30%, it is one of the most prevalent ...

CervicoXNet: an automated cervicogram interpretation network.

Visual inspection with acetic acid (VIA) is a pre-cancerous screening program for low-middle-income countries (LMICs). Due to the limited number of on...

Growing pains: strategies for improving ergonomics in minimally invasive gynecologic surgery.

PURPOSE OF REVIEW: To evaluate factors contributing to the development of work-related musculoskeletal disorders (WMSDs) and review strategies for mit...

A Deep Learning-Based System Trained for Gastrointestinal Stromal Tumor Screening Can Identify Multiple Types of Soft Tissue Tumors.

The accuracy and timeliness of the pathologic diagnosis of soft tissue tumors (STTs) critically affect treatment decision and patient prognosis. Thus,...

Bubble-Based Microrobots with Rapid Circular Motions for Epithelial Pinning and Drug Delivery.

Remotely powered microrobots are proposed as next-generation vehicles for drug delivery. However, most microrobots swim with linear trajectories and l...

Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis.

OBJECTIVE: Ovarian cancer is a significant health issue with lasting impacts on the community. Despite recent advances in surgical, chemotherapeutic a...

Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.

Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer...

Label-free liquid biopsy through the identification of tumor cells by machine learning-powered tomographic phase imaging flow cytometry.

Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Bi...

Development and validation of a deep learning survival model for cervical adenocarcinoma patients.

BACKGROUND: The aim was to develop a personalized survival prediction deep learning model for cervical adenocarcinoma patients and process personalize...

Interpretable attention-based deep learning ensemble for personalized ovarian cancer treatment without manual annotations.

Inhibition of pathological angiogenesis has become one of the first FDA approved targeted therapies widely tested in anti-cancer treatment, i.e. VEGF-...

A probabilistic deep learning model of inter-fraction anatomical variations in radiotherapy.

. In radiotherapy, the internal movement of organs between treatment sessions causes errors in the final radiation dose delivery. To assess the need f...

Application of artificial intelligence centric workflows for evaluation of neuroradiology emergencies.

The goal of this study was to perform a pilot study to assess user-interface of radiologists with an artificial-intelligence (AI) centric workflow for...

An ultrasound-based deep learning radiomic model combined with clinical data to predict clinical pregnancy after frozen embryo transfer: a pilot cohort study.

RESEARCH QUESTION: Can a multi-modal fusion model based on ultrasound-based deep learning radiomics combined with clinical parameters provide personal...

Imaging of Neck Nodes in Head and Neck Cancers - a Comprehensive Update.

Cervical lymph node metastases from head and neck squamous cell cancers significantly reduce disease-free survival and worsen overall prognosis and, h...

Treatment of the Paretic Hand with a Robotic Glove Combined with Physiotherapy in a Patient Suffering from Traumatic Tetraparesis: A Case Report.

BACKGROUND: cervical spinal cord injury leads to loss of upper limb functionality, which causes a decrease in autonomy to perform activities of daily ...