Endocrinology

Menopause

Latest AI and machine learning research in menopause for healthcare professionals.

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Association of Vitamin D and Parathyroid Hormone Levels in Overweight and Obese Adolescents.

Vitamin D deficiency in known to be high in obese and overweight adolescents. Few studies in other c...

A novel integrated action crossing method for drug-drug interaction prediction in non-communicable diseases.

BACKGROUND AND OBJECTIVE: Drug-drug interaction (DDI) is one of the main causes of toxicity and trea...

Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer.

BACKGROUND: Gene-expression companion diagnostic tests, such as the Oncotype DX test, assess the ris...

Using machine-learning approaches to predict non-participation in a nationwide general health check-up scheme.

BACKGROUND: In the time since the launch of a nationwide general health check-up and instruction pro...

Evaluation of computational techniques for predicting non-synonymous single nucleotide variants pathogenicity.

The human genetic diseases associated with many factors, one of these factors is the non-synonymous ...

A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.

BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, wit...

Annotating Diseases Using Human Phenotype Ontology Improves Prediction of Disease-Associated Long Non-coding RNAs.

Recently, many long non-coding RNAs (lncRNAs) have been identified and their biological function has...

Modeling Dengue vector population using remotely sensed data and machine learning.

Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main ve...

Prediction of plant lncRNA by ensemble machine learning classifiers.

BACKGROUND: In plants, long non-protein coding RNAs are believed to have essential roles in developm...

Evolution of upper limb kinematics four years after subacute robot-assisted rehabilitation in stroke patients.

To assess functional status and robot-based kinematic measures four years after subacute robot-assi...

Machine learning to predict the occurrence of bisphosphonate-related osteonecrosis of the jaw associated with dental extraction: A preliminary report.

INTRODUCTION: The aim of this study was to build and validate five types of machine learning models ...

Endocardial linear infarct exclusion technique for non-ischaemic functional mitral regurgitation caused by cardiac sarcoidosis: a case report.

INTRODUCTION: Damage to the posterior wall of the left ventricle (LV) can cause tethering mitral reg...

Learning-based endovascular navigation through the use of non-rigid registration for collaborative robotic catheterization.

PURPOSE: Endovascular intervention is limited by two-dimensional intraoperative imaging and prolonge...

Identifying tumor in pancreatic neuroendocrine neoplasms from Ki67 images using transfer learning.

The World Health Organization (WHO) has clear guidelines regarding the use of Ki67 index in defining...

Early robot-assisted gait retraining in non-ambulatory patients with stroke: a single blind randomized controlled trial.

BACKGROUND: Restoration of walking function is a primary concern of neurorehabilitation with respect...

Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques.

The establishment and improvement of transmission systems rely on models that take into account, (am...

An efficient, large-scale, non-lattice-detection algorithm for exhaustive structural auditing of biomedical ontologies.

One of the basic challenges in developing structural methods for systematic audition on the quality ...

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