Obstetrics & Gynecology

Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.

PURPOSE: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.

Cervical cell recognition based on AGVF-Snake algorithm.

PURPOSE: In recent years, with the increasing incidence of cervical cancer, it is a tedious and time-consuming task with unsatisfying accuracy to manually recognize the cells. Machine recognition can be a good solution, but it suffers from the difficulty of obtaining precise edges of cells, which directly influence the final recognition accuracy. To improve the recognition accuracy and shorten the...

Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy.

Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. S...

Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied ...

Binary tree-like network with two-path Fusion Attention Feature for cervical cell nucleus segmentation.

Early detection of cervical lesion is of great significance in reducing mortality from cervical cancer, and segmentation of cervical cell nuclei plays...

CytoProcessorTM: A New Cervical Cancer Screening System for Remote Diagnosis.

BACKGROUND: Current automated cervical cytology screening systems still heavily depend on manipulation of glass slides. We developed a new system call...

Classification and Recognition of Ovarian Cells Based on Two-Dimensional Light Scattering Technology.

Ovarian cancer is a very insidious malignant tumor. In order to detect ovarian cancer cells early, the classification and recognition of ovarian cance...

Machine Learning for the Prediction of Cervical Spondylotic Myelopathy: A Post Hoc Pilot Study of 28 Participants.

BACKGROUND: Cervical spondylotic myelopathy (CSM) severity and presence of symptoms are often difficult to predict based simply on clinical imaging al...

Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape.

Artificial intelligence (AI) has made impressive strides recently in interpreting complex images, thanks to improvements in deep learning techniques a...

Swarm-Fuzzy Rule-Based Targeted Nano Delivery Using Bioinspired Nanomachines.

Cooperative navigation and swarm decision making take center stage in a broad range of distributed applications with high-environmental and measuremen...

Prediction of fetal state from the cardiotocogram recordings using neural network models.

The combination of machine vision and soft computing approaches in the clinical decisions, using training data, can improve medical decisions and trea...

Prediction of cervical spine injury in young pediatric patients: an optimal trees artificial intelligence approach.

BACKGROUND: Cervical spine injuries (CSI) are a major concern in young pediatric trauma patients. The consequences of missed injuries and difficulties...

Machine learning for the prediction of postpartum complications is promising, but needs rigorous evaluation.

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT.

PURPOSE: To develop a deep learning-based computer-aided diagnosis (CAD) system for use in the CT diagnosis of cervical lymph node metastasis (LNM) in...

Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods.

OBJECTIVES: The aim of this study was to develop a new prognostic classification for epithelial ovarian cancer (EOC) patients using gradient boosting ...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC.

Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for numerous potential applications. They have great p...

New perspectives about the role of robot-assisted surgery for the treatment of endometriosis.

Robot-assisted Therapy for the Upper Limb after Cervical Spinal Cord Injury.

Tetraplegia resulting from cervical injury is the most frequent neurologic category after spinal cord injury and causes substantial disability. The re...

Using natural language processing and machine learning to classify health literacy from secure messages: The ECLIPPSE study.

Limited health literacy is a barrier to optimal healthcare delivery and outcomes. Current measures requiring patients to self-report limitations are t...

Vision-aided brain-machine interface training system for robotic arm control and clinical application on two patients with cervical spinal cord injury.

BACKGROUND: While spontaneous robotic arm control using motor imagery has been reported, most previous successful cases have used invasive approaches ...