Obstetrics & Gynecology

Molecular imaging and deep learning analysis of uMUC1 expression in response to chemotherapy in an orthotopic model of ovarian cancer.

Artificial Intelligence (AI) algorithms including deep learning have recently demonstrated remarkable progress in image-recognition tasks. Here, we utilized AI for monitoring the expression of underglycosylated mucin 1 (uMUC1) tumor antigen, a biomarker for ovarian cancer progression and response to therapy, using contrast-enhanced in vivo imaging. This was done using a dual-modal (magnetic resona...

Synthesis of diagnostic quality cancer pathology images by generative adversarial networks.

Deep learning-based computer vision methods have recently made remarkable breakthroughs in the analysis and classification of cancer pathology images. However, there has been relatively little investigation of the utility of deep neural networks to synthesize medical images. In this study, we evaluated the efficacy of generative adversarial networks to synthesize high-resolution pathology images o...

Evidence of profound ovarian suppression on combined hormonal contraception resulting in dramatically different ovarian reserve testing and oocyte retrieval outcomes: case report and review of the literature.

OBJECTIVE: To describe a case report and demonstrate that degree of ovarian suppression with continuous combined hormonal contraception (CHC) may be m...

ASO Author Reflections: Robotic Radical Hysterectomy for Patients with Early-Stage Cervical Cancer: Oncologic Outcomes.

Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Traditionally, cell proliferation is quantified by lab...

Using machine learning for predicting cervical cancer from Swedish electronic health records by mining hierarchical representations.

Electronic health records (EHRs) contain rich documentation regarding disease symptoms and progression, but EHR data is challenging to use for diagnos...

Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.

Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout mu...

Establishment and Analysis of a Combined Diagnostic Model of Polycystic Ovary Syndrome with Random Forest and Artificial Neural Network.

Polycystic ovary syndrome (PCOS) is one of the most common metabolic and reproductive endocrinopathies. However, few studies have tried to develop a d...

Classifying the type of delivery from cardiotocographic signals: A machine learning approach.

BACKGROUND AND OBJECTIVE: Cardiotocography (CTG) is the most employed methodology to monitor the foetus in the prenatal phase. Since the evaluation of...

Deep learning-based fetoscopic mosaicking for field-of-view expansion.

PURPOSE: Fetoscopic laser photocoagulation is a minimally invasive surgical procedure used to treat twin-to-twin transfusion syndrome (TTTS), which in...

Artificial intelligence-assisted cytology for detection of cervical intraepithelial neoplasia or invasive cancer: A multicenter, clinical-based, observational study.

OBJECTIVE: Artificial intelligence (AI) could automatedly detect abnormalities in digital cytological images, however, the effect in cervical cancer s...

Time-series cardiovascular risk factors and receipt of screening for breast, cervical, and colon cancer: The Guideline Advantage.

BACKGROUND: Cancer is the second leading cause of death in the United States. Cancer screenings can detect precancerous cells and allow for earlier di...

Classification of cervical neoplasms on colposcopic photography using deep learning.

Colposcopy is widely used to detect cervical cancers, but experienced physicians who are needed for an accurate diagnosis are lacking in developing co...

A Linear Regression and Deep Learning Approach for Detecting Reliable Genetic Alterations in Cancer Using DNA Methylation and Gene Expression Data.

DNA methylation change has been useful for cancer biomarker discovery, classification, and potential treatment development. So far, existing methods u...

A Proxy for Detecting IUGR Based on Gestational Age Estimation in a Guatemalan Rural Population.

progress of fetal development is normally assessed through manual measurements taken from ultrasound images, requiring relatively expensive equipment...

Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.

Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovar...

Congenital Hypothyroidism due to a Low Level of Maternal Thyrotropin Receptor-Blocking Antibodies.

INTRODUCTION: Maternal TSH receptor antibodies (TRAbs) can cross the placenta and affect fetal and neonatal thyroid function. Maternal TSH receptor-bl...

Assessment of Magnetic Liposomal Paclitaxel Nanoparticles as a Potential Carrier for the Treatment of Ovarian Cancer.

This study aimed to evaluate the role of magnetic liposome nanoparticles (ML NPs) as a carrier for paclitaxel (PTX) for the treatment of ovarian canc...

Investigation of the Dose-Enhancement Effects of Spherical and Rod-Shaped Gold Nanoparticles on the HeLa Cell Line.

BACKGROUND: Cervical cancer cells are known as radioresistant cells. Current treatment methods have not improved the patients' survival efficiently; t...

Discovery of different metabotypes in overconditioned dairy cows by means of machine learning.

Using data from targeted metabolomics in serum in combination with machine learning (ML) approaches, we aimed at (1) identifying divergent metabotypes...