Endocrinology

Menopause

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

5,024 articles
Stay Ahead - Weekly Menopause research updates
Subscribe
Browse Categories
Showing 1198-1218 of 5,024 articles
Improvement of Patient Classification Using Feature Selection Applied to Bidirectional Axial Transmission.

Osteoporosis is still a worldwide problem, particularly due to associated fragility fractures. Patie...

Minimize Tracking Occlusion in Collaborative Pick-and-Place Tasks: An Analytical Approach for Non-Wrist-Partitioned Manipulators.

Several industrial pick-and-place applications, such as collaborative assembly lines, rely on visual...

An Artificial Neural Network-Based Approach to Optimizing Energy Efficiency in Residential Buildings in Hot Summer and Cold Winter Regions.

Resource depletion and ecological crisis have prompted human beings to reflect on the behavior patte...

Danshao Shugan Granule therapy for non-alcoholic fatty liver disease.

BACKGROUND: Danshao Shugan Granules (DSSG), a traditional Chinese medicine (TCM), is given to protec...

Nuclear morphology is a deep learning biomarker of cellular senescence.

Cellular senescence is an important factor in aging and many age-related diseases, but understanding...

Linear or non-linear multivariate calibration models? That is the question.

Concepts from data science, machine learning, deep learning and artificial neural networks are sprea...

Non-destructive detection and classification of textile fibres based on hyperspectral imaging and 1D-CNN.

Textile fibre is very common in daily life, and its classification and identification play an import...

TSDLPP: A Novel Two-Stage Deep Learning Framework For Prognosis Prediction Based on Whole Slide Histopathological Images.

Recently, digital pathology image-based prognosis prediction has become a hot topic in healthcare re...

Towards Trustworthy Energy Disaggregation: A Review of Challenges, Methods, and Perspectives for Non-Intrusive Load Monitoring.

Non-intrusive load monitoring (NILM) is the task of disaggregating the total power consumption into ...

Osteoporosis screening support system from panoramic radiographs using deep learning by convolutional neural network.

OBJECTIVES: This study was performed to develop computer-aided screening systems that could predict ...

Deep-Learning-Based Ultrasound Sound-Speed Tomography Reconstruction with Tikhonov Pseudo-Inverse Priori.

Ultrasound sound-speed tomography (USST) is a promising technology for breast imaging and breast can...

Best of Both Worlds: Detecting Application Layer Attacks through 802.11 and Non-802.11 Features.

Intrusion detection in wireless and, more specifically, Wi-Fi networks is lately increasingly under ...

Machine learning-assisted prediction of pneumonia based on non-invasive measures.

BACKGROUND: Pneumonia is an infection of the lungs that is characterized by high morbidity and morta...

Physics guided neural networks for modelling of non-linear dynamics.

The success of the current wave of artificial intelligence can be partly attributed to deep neural n...

Mean-square stabilization of impulsive neural networks with mixed delays by non-fragile feedback involving random uncertainties.

In this paper, we consider a class of neural networks with mixed delays and impulsive interferences....

Comparison of Two-Port and Three-Port Approaches in Robotic Lobectomy for Non-Small Cell Lung Cancer.

BACKGROUND: Robot-assisted lobectomy has been used to treat non-small cell lung cancer and usually u...

Detecting the sources of chemicals in the Black Sea using non-target screening and deep learning convolutional neural networks.

The Black Sea is an important ecosystem, which is affected by various anthropogenic pressures, such ...

Can machine learning predict pharmacotherapy outcomes? An application study in osteoporosis.

BACKGROUND AND OBJECTIVE: The specific aim of this study is to develop machine learning models as a ...

Browse Categories