Endocrinology

Menopause

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

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Early prognosis prediction for non-variceal upper gastrointestinal bleeding in the intensive care unit: based on interpretable machine learning.

INTRODUCTION: This study aims to construct a mortality prediction model for patients with non-varice...

Estimating lumbar bone mineral density from conventional MRI and radiographs with deep learning in spine patients.

PURPOSE: This study aimed to develop machine learning methods to estimate bone mineral density and d...

Deep-learning-based method for the segmentation of ureter and renal pelvis on non-enhanced CT scans.

This study aimed to develop a deep-learning (DL) based method for three-dimensional (3D) segmentatio...

Machine learning-powered wearable interface for distinguishable and predictable sweat sensing.

The constrained resources on wearable devices pose a challenge in meeting the demands for comprehens...

Retrospective validation study of a machine learning-based software for empirical and organism-targeted antibiotic therapy selection.

UNLABELLED: Errors in antibiotic prescriptions are frequent, often resulting from the inadequate cov...

Advanced rehabilitation in ischaemic stroke research.

At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke...

A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases.

Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There ...

Non-coplanar CBCT image reconstruction using a generative adversarial network for non-coplanar radiotherapy.

PURPOSE: To develop a non-coplanar cone-beam computed tomography (CBCT) image reconstruction method ...

Digital Biomarker for Muscle Function Assessment Using Surface Electromyography With Electrical Stimulation and a Non-Invasive Wearable Device.

Sarcopenia is a comprehensive degenerative disease with the progressive loss of skeletal muscle mass...

Machine learning for (non-)epileptic tissue detection from the intraoperative electrocorticogram.

OBJECTIVE: Clinical visual intraoperative electrocorticography (ioECoG) reading intends to localize ...

Diagnostic accuracy of artificial intelligence models in detecting osteoporosis using dental images: a systematic review and meta-analysis.

The current study aimed to systematically review the literature on the accuracy of artificial intell...

Understanding and mitigating dimensional collapse of Graph Contrastive Learning: A non-maximum removal approach.

Graph Contrastive Learning (GCL) generates graph-level embeddings by maximizing Mutual Information b...

Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer.

BACKGROUND: Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive...

Diagnostic accuracy of chest X-ray and CT using artificial intelligence for osteoporosis: systematic review and meta-analysis.

INTRODUCTION: Artificial intelligence (AI)-based systems using chest images are potentially reliable...

Non-Intrusive System for Honeybee Recognition Based on Audio Signals and Maximum Likelihood Classification by Autoencoder.

Artificial intelligence and Internet of Things are playing an increasingly important role in monitor...

Preovulatory progesterone levels are the top indicator for ovulation prediction based on machine learning model evaluation: a retrospective study.

BACKGROUND: Accurately predicting ovulation timing is critical for women undergoing natural cycle-fr...

Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

BACKGROUND: Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoho...

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