Obstetrics & Gynecology

Predicting risk of obesity and meal planning to reduce the obese in adulthood using artificial intelligence.

BACKGROUND: An unhealthy diet or excessive amount of food intake creates obesity issues in human beings that further may cause several diseases such as Polycystic Ovary Syndrome (PCOS), Cardiovascular disease, Diabetes, Cancers, etc. Obesity is a major risk factor for PCOS, which is a common disease in women and is significantly correlated with weight gain.

Ovarian tumor diagnosis using deep convolutional neural networks and a denoising convolutional autoencoder.

Discrimination of ovarian tumors is necessary for proper treatment. In this study, we developed a convolutional neural network model with a convolutional autoencoder (CNN-CAE) to classify ovarian tumors. A total of 1613 ultrasound images of ovaries with known pathological diagnoses were pre-processed and augmented for deep learning analysis. We designed a CNN-CAE model that removes the unnecessary...

Automatic Detection and Segmentation of Ovarian Cancer Using a Multitask Model in Pelvic CT Images.

Ovarian cancer is one of the most common malignant tumours of female reproductive organs in the world. The pelvic CT scan is a common examination meth...

Prediction Model of Residual Neural Network for Pathological Confirmed Lymph Node Metastasis of Ovarian Cancer.

PURPOSE: We want to develop a model for predicting lymph node status based on positron emission computed tomography (PET) images of untreated ovarian ...

Research on the Guidance of Youth Labor Education Based on the "Combination of Education and Production Labor" Program Based on the Deep Learning Model.

At present, there is a lack of research on Marx's idea of "combining education and productive labor" and its guiding significance for youth labor educ...

Modeling the transplacental transfer of small molecules using machine learning: a case study on per- and polyfluorinated substances (PFAS).

BACKGROUND: Despite their large numbers and widespread use, very little is known about the extent to which per- and polyfluoroalkyl substances (PFAS) ...

Deep-learning model associating lateral cervical radiographic features with Cormack-Lehane grade 3 or 4 glottic view.

Unanticipated difficult laryngoscopy is associated with serious airway-related complications. We aimed to develop and test a convolutional neural netw...

Ergonomic Assessment of the Surgeon's Physical Workload During Robot-Assisted Versus Standard Laparoscopy in a French Multicenter Randomized Trial (ROBOGYN-1004 Trial).

BACKGROUND: Standard laparoscopy (SL) is responsible for musculoskeletal disorders in surgeons because of poor ergonomic positions, which could be red...

Artificial Intelligence-Based Detection of Human Embryo Components for Assisted Reproduction by In Vitro Fertilization.

Assisted reproductive technology is helping humans by addressing infertility using different medical procedures that help in a successful pregnancy. I...

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessm...

Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning.

Clinical guidelines recommend several risk factors to identify women in early pregnancy at high risk of developing pregnancy-associated hypertension. ...

Comparison of Deep Learning and Classical Machine Learning Algorithms to Predict Postoperative Outcomes for Anterior Cervical Discectomy and Fusion Procedures With State-of-the-art Performance.

STUDY DESIGN: Retrospective cohort.

Application and Communication Optimization Technology of Unmanned Distribution Car under Deep Learning in Logistics Express of COVID-19.

This work aims to solve the problem that the daily necessities of urban residents cannot be delivered during coronavirus disease 2019 (COVID-19), ther...

Reappraisal of Robotic Assistance in Gynecologic Oncology: The Lessons of ROBOGYN-1004.

Prediction of placenta accreta spectrum by combining deep learning and radiomics using T2WI: a multicenter study.

PURPOSE: To achieve prenatal prediction of placenta accreta spectrum (PAS) by combining clinical model, radiomics model, and deep learning model using...

Spinal robotics in cervical spine surgery: a systematic review with key concepts and technical considerations.

OBJECTIVE: Spinal robotics for thoracolumbar procedures, predominantly employed for the insertion of pedicle screws, is currently an emerging topic in...

Machine learning in project analytics: a data-driven framework and case study.

The analytic procedures incorporated to facilitate the delivery of projects are often referred to as project analytics. Existing techniques focus on r...

Exploring the Application of BIM Technology in the Whole Process of Construction Cost Management with Computational Intelligence.

The construction industry is a labor-intensive industry in China. In recent years, as people's living standards have risen, so have their requirements...

Differentiating single cervical cells by mitochondrial fluorescence imaging and deep learning-based label-free light scattering with multi-modal static cytometry.

Cervical cancer is a high-risk disease that threatens women's health globally. In this study, we developed the multi-modal static cytometry that adopt...

Machine learning applications in gynecological cancer: A critical review.

Machine Learning (ML) represents a computer science capable of generating predictive models, by exposure to raw, training data, without being rigidly ...