Endocrinology

Menopause

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

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Gene set analysis methods for the functional interpretation of non-mRNA data-Genomic range and ncRNA data.

Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics s...

Comparison between atlas and convolutional neural network based automatic segmentation of multiple organs at risk in non-small cell lung cancer.

Delineation of organs at risk (OARs) is important but time consuming for radiotherapy planning. Auto...

Assisting the Non-invasive Diagnosis of Liver Fibrosis Stages using Machine Learning Methods.

Fibrosis is a significant indication of chronic liver diseases often due to hepatitis C Virus. It is...

Deformable US/CT Image Registration with a Convolutional Neural Network for Cardiac Arrhythmia Therapy.

Image registration represents one of the fundamental techniques in medical imaging and image-guided ...

Classifying non-small cell lung cancer types and transcriptomic subtypes using convolutional neural networks.

OBJECTIVE: Non-small cell lung cancer is a leading cause of cancer death worldwide, and histopatholo...

PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins.

MOTIVATION: Gram-positive bacteria have developed secretion systems to transport proteins across the...

Efficacy of an Automated Robotic Cleaning Device for Compounding Pharmacies.

Compounded medicinal products should be prepared using an appropriate quality-assurance system. Clea...

Diagnosis of Osteoporosis using modified U-net architecture with attention unit in DEXA and X-ray images.

BACKGROUND: Osteoporosis, a silent killing disease of fracture risk, is normally determined based on...

CHDGKB: a knowledgebase for systematic understanding of genetic variations associated with non-syndromic congenital heart disease.

Congenital heart disease (CHD) is one of the most common birth defects, with complex genetic and env...

Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis.

With the continuous development of artificial intelligence (AI) technology, big data-supported AI te...

Recent Advances on the Semi-Supervised Learning for Long Non-Coding RNA-Protein Interactions Prediction: A Review.

In recent years, more and more evidence indicates that long non-coding RNA (lncRNA) plays a signific...

Application of Machine Learning Methods in Predicting Nuclear Receptors and their Families.

Nuclear receptors (NRs) are a superfamily of ligand-dependent transcription factors that are closely...

circDeep: deep learning approach for circular RNA classification from other long non-coding RNA.

MOTIVATION: Over the past two decades, a circular form of RNA (circular RNA), produced through alter...

Deep convolutional neural network for reduction of contrast-enhanced region on CT images.

This study aims to produce non-contrast computed tomography (CT) images using a deep convolutional n...

Machine-Learning and Stochastic Tumor Growth Models for Predicting Outcomes in Patients With Advanced Non-Small-Cell Lung Cancer.

PURPOSE: The prediction of clinical outcomes for patients with cancer is central to precision medici...

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