Endocrinology

Menopause

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

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Application of MALDI-TOF MS and machine learning for the detection of SARS-CoV-2 and non-SARS-CoV-2 respiratory infections.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) could ai...

Machine vision-based non-destructive dissolution prediction of meloxicam-containing tablets.

Machine vision systems have emerged for quality assessment of solid dosage forms in the pharmaceutic...

Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction.

The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-res...

Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improv...

An accurately supervised motion-aware deep network for non-contact pain assessment of trigeminal neuralgia mouse model.

Pain assessment in trigeminal neuralgia (TN) mouse models is essential for exploring its pathophysio...

Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence.

BACKGROUND: Diabetic Retinopathy (DR) is a leading cause of blindness worldwide, affecting people wi...

Improved Arterial Stiffness Indices 3 and 6 Months after Living-donor Renal Transplantation.

Arterial stiffness is a non-traditional risk factor of cardiovascular disease and may explain part o...

Cine-cardiac magnetic resonance to distinguish between ischemic and non-ischemic cardiomyopathies: a machine learning approach.

OBJECTIVE: This work aimed to derive a machine learning (ML) model for the differentiation between i...

Colorectal procedures with the novel Hugo™ RAS system: training process and case series report from a non-robotic surgical team.

BACKGROUND: The landscape of robotic surgery is evolving with the emergence of new platforms. Howeve...

Development, validation, and transportability of several machine-learned, non-exercise-based VO prediction models for older adults.

BACKGROUND: There exist few maximal oxygen uptake (VO) non-exercise-based prediction equations, fewe...

End-to-end multimodal 3D imaging and machine learning workflow for non-destructive phenotyping of grapevine trunk internal structure.

Quantifying healthy and degraded inner tissues in plants is of great interest in agronomy, for examp...

Deep learning-based harmonization of trabecular bone microstructures between high- and low-resolution CT imaging.

BACKGROUND: Osteoporosis is a bone disease related to increased bone loss and fracture-risk. The var...

A deep learning based holistic diagnosis system for immunohistochemistry interpretation and molecular subtyping.

BACKGROUND: Breast cancer in different molecular subtypes, which is determined by the overexpression...

TCDformer: A transformer framework for non-stationary time series forecasting based on trend and change-point detection.

Although time series prediction models based on Transformer architecture have achieved significant a...

Modelling the GDP of KSA using linear and non-linear NNAR and hybrid stochastic time series models.

BACKGROUND: Gross domestic product (GDP) serves as a crucial economic indicator for measuring a coun...

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