Endocrinology

Menopause

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

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Non-Standardized Patch-Based ECG Lead Together With Deep Learning Based Algorithm for Automatic Screening of Atrial Fibrillation.

This study was to assess the feasibility of using non-standardized single-lead electrocardiogram (EC...

Overall survival prediction of non-small cell lung cancer by integrating microarray and clinical data with deep learning.

Non-small cell lung cancer (NSCLC) is one of the most common lung cancers worldwide. Accurate progno...

Statistical Modeling of Longitudinal Data with Non-ignorable Non-monotone Missingness with Semiparametric Bayesian and Machine Learning Components.

In longitudinal studies, outcomes are measured repeatedly over time and it is common that not all th...

Recognition of Common Non-Normal Walking Actions Based on Relief-F Feature Selection and Relief-Bagging-SVM.

Action recognition algorithms are widely used in the fields of medical health and pedestrian dead re...

Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer.

DNA methylation of various genomic regions has been found to be associated with gene expression in d...

End-to-end semantic segmentation of personalized deep brain structures for non-invasive brain stimulation.

Electro-stimulation or modulation of deep brain regions is commonly used in clinical procedures for ...

Effects of Deep Learning Reconstruction Technique in High-Resolution Non-contrast Magnetic Resonance Coronary Angiography at a 3-Tesla Machine.

PURPOSE: To evaluate the effects of deep learning reconstruction (DLR) in qualitative and quantitati...

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In th...

Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures deri...

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.

INTRODUCTION: The aim of the study was to extract anthropometric measures from CT by deep learning a...

Control of hyperparathyroidism with the intravenous calcimimetic etelcalcetide in dialysis patients adherent and non-adherent to oral calcimimetics.

BACKGROUND: In dialysis patients, non-adherence to oral cinacalcet adds complexity to the control of...

Decoding rejuvenating effects of mechanical loading on skeletal aging using in vivo μCT imaging and deep learning.

Throughout the process of aging, dynamic changes of bone material, micro- and macro-architecture res...

Radiomics for classification of bone mineral loss: A machine learning study.

PURPOSE: The purpose of this study was to develop predictive models to classify osteoporosis, osteop...

Reconstruction of undersampled 3D non-Cartesian image-based navigators for coronary MRA using an unrolled deep learning model.

PURPOSE: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using a...

Machine Learning for Detecting Early Infarction in Acute Stroke with Non-Contrast-enhanced CT.

Background Identifying the presence and extent of infarcted brain tissue at baseline plays a crucial...

Deep Learning-Based Development of Personalized Human Head Model With Non-Uniform Conductivity for Brain Stimulation.

Electromagnetic stimulation of the human brain is a key tool for neurophysiological characterization...

DeepSnap-Deep Learning Approach Predicts Progesterone Receptor Antagonist Activity With High Performance.

The progesterone receptor (PR) is important therapeutic target for many malignancies and endocrine d...

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavo...

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