Endocrinology

Menopause

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

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The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.

Epilepsy surgery is effective for patients with medication-resistant seizures, however 20-40% of the...

Prediction of tuberculosis clusters in the riverine municipalities of the Brazilian Amazon with machine learning.

OBJECTIVE: Tuberculosis (TB) is the second most deadly infectious disease globally, posing a signifi...

Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.

RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning...

Deep learning segmentation of non-perfusion area from color fundus images and AI-generated fluorescein angiography.

The non-perfusion area (NPA) of the retina is an important indicator in the visual prognosis of pati...

Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF.

Immunopeptidomics is crucial for immunotherapy and vaccine development. Because the generation of im...

BACK-to-MOVE: Machine learning and computer vision model automating clinical classification of non-specific low back pain for personalised management.

BACKGROUND: Low back pain (LBP) is a major global disability contributor with profound health and so...

Machine learning-based algorithm identifies key mitochondria-related genes in non-alcoholic steatohepatitis.

BACKGROUND: Evidence suggests that hepatocyte mitochondrial dysfunction leads to abnormal lipid meta...

Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques.

Discriminating different cultivars of maca powder (MP) and detecting their authenticity after adulte...

Detection of Non-Sustained Supraventricular Tachycardia in Atrial Fibrillation Screening.

OBJECTIVE: Non-sustained supraventricular tachycardia (nsSVT) is associated with a higher risk of de...

Skin Conductance-Based Acupoint and Non-Acupoint Recognition Using Machine Learning.

Acupoints (APs) prove to have positive effects on disease diagnosis and treatment, while intelligent...

ML3CNet: Non-local means-assisted automatic framework for lung cancer subtypes classification using histopathological images.

BACKGROUND AND OBJECTIVE: Lung cancer (LC) has a high fatality rate that continuously affects human ...

Detecting the symptoms of Parkinson's disease with non-standard video.

BACKGROUND: Neurodegenerative diseases, such as Parkinson's disease (PD), necessitate frequent clini...

Automatic Skeleton Segmentation in CT Images Based on U-Net.

Bone metastasis, emerging oncological therapies, and osteoporosis represent some of the distinct cli...

Differentiating Epileptic and Psychogenic Non-Epileptic Seizures Using Machine Learning Analysis of EEG Plot Images.

The treatment of epilepsy, the second most common chronic neurological disorder, is often complicate...

Optimizing Human-Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis.

The transition to Industry 4.0 and 5.0 underscores the need for integrating humans into manufacturin...

The role of artificial intelligence and fintech in promoting eco-friendly investments and non-greenwashing practices in the US market.

This study explores the intricate connections among financial technology (FinTech), artificial intel...

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