Endocrinology

Menopause

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

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Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep convolutional neural networks. In this study, we compared sCTs based on CBCTs and MRs for head and neck (H&N) cancer patients in terms of image quality...

Dec 5 2020 33179874

Bone Mineral Density and Content Among Patients With Coronary Artery Disease: A Comparative Study.

INTRODUCTION: Some studies indicate an association between coronary artery disease (CAD) and osteoporosis. This case-control study examined the association between body composition and bone mineral content (BMC) and density (BMD) among patients with CAD.

Nov 23 2020 33892918
Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer.

We apply for the first-time interpretable deep learning methods simultaneously to the most common skin cancers (basal cell carcinoma, squamous cell ca...

Nov 21 2020 33260112
Dose-dependent effects of ultrasound therapy on hepatocellular carcinoma.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation therapy require increased tumor perfusion for a b...

Nov 17 2020 34188756
Effect of Chronotherapy of Antihypertensives in Chronic Kidney Disease: A Randomized Control Trial.

INTRODUCTION: There is a higher prevalence of non-dipping pattern in hypertensive chronic kidney disease (CKD) patients. Nocturnal hypertension has be...

Nov 11 2020 33994681
Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates.

This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic perf...

Nov 10 2020 33182778
Comprehensive evaluation of the combined extracts of Epimedii Folium and Ligustri Lucidi Fructus for PMOP in ovariectomized rats based on MLP-ANN methods.

ETHNOPHARMACOLOGICAL RELEVANCE: Kidney deficiency is the main pathogenesis of osteoporosis based on the theory of "kidney governing bones" in traditio...

Nov 8 2020 33176184
A Comprehensive Analysis of MicroRNAs in Human Osteoporosis.

MicroRNAs (miRNAs) are single-stranded RNA molecules that control gene expression in various processes, such as cancers, Alzheimer's disease, and bone...

Oct 21 2020 33193074
Deep Learning With Electronic Health Records for Short-Term Fracture Risk Identification: Crystal Bone Algorithm Development and Validation.

BACKGROUND: Fractures as a result of osteoporosis and low bone mass are common and give rise to significant clinical, personal, and economic burden. E...

Oct 16 2020 32956069
Non-invasive decision support for NSCLC treatment using PET/CT radiomics.

Two major treatment strategies employed in non-small cell lung cancer, NSCLC, are tyrosine kinase inhibitors, TKIs, and immune checkpoint inhibitors, ...

Oct 16 2020 33067442
Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature.

Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strong potential for furthe...

Oct 2 2020 33006554
Opportunistic osteoporosis screening in multi-detector CT images using deep convolutional neural networks.

OBJECTIVE: To explore the application of deep learning in patients with primary osteoporosis, and to develop a fully automatic method based on deep co...

Oct 1 2020 33001308
Machine Learning Outcome Prediction in Dilated Cardiomyopathy Using Regional Left Ventricular Multiparametric Strain.

The clinical presentation of idiopathic dilated cardiomyopathy (IDCM) heart failure (HF) patients who will respond to medical therapy (responders) and...

Oct 1 2020 33006006
Peginterferon and Entecavir Combination Therapy Improves Outcome of Non-Early Response Hepatitis B e Antigen-Positive Patients.

BACKGROUND: The efficacy of nucleot(s)ide analogs (NAs) and pegylated interferon (PegIFN) combination therapy for hepatitis B e antigen-positive (HBeA...

Sep 30 2020 33889654
Clinical evaluation of atlas- and deep learning-based automatic segmentation of multiple organs and clinical target volumes for breast cancer.

Manual segmentation is the gold standard method for radiation therapy planning; however, it is time-consuming and prone to inter- and intra-observer v...

Sep 28 2020 32991916
Classification of estrogenic compounds by coupling high content analysis and machine learning algorithms.

Environmental toxicants affect human health in various ways. Of the thousands of chemicals present in the environment, those with adverse effects on t...

Sep 24 2020 32970665
Democratizing AI: non-expert design of prediction tasks.

Non-experts have long made important contributions to machine learning (ML) by contributing training data, and recent work has shown that non-experts ...

Sep 7 2020 33816947
Artificial Intelligence-Based Quantification of Epithelial Proliferation in Mammary Glands of Rats and Oviducts of Göttingen Minipigs.

Quantitative assessment of proliferation can be an important endpoint in toxicologic pathology. Traditionally, cell proliferation is quantified by lab...

Aug 25 2020 32840183
Applications of Artificial Intelligence in Musculoskeletal Imaging: From the Request to the Report.

Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists...

Aug 18 2020 32809857
Predictive modeling of estrogen receptor agonism, antagonism, and binding activities using machine- and deep-learning approaches.

As defined by the World Health Organization, an endocrine disruptor is an exogenous substance or mixture that alters function(s) of the endocrine syst...

Aug 10 2020 32778734
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