Endocrinology

Menopause

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

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Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.

PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, ...

Social Robots as a Complementary Therapy in Chronic, Progressive Diseases.

Globally, the world population is ageing, which increases the prevalence of non-communicable disease...

DOES THE 25-OH-VITAMIN D LEVEL AFFECT THE INSULIN RESISTANCE IN THE PATIENTS WITH NON-DIABETIC CHRONIC KIDNEY DISEASE?

INTRODUCTION: The aim of this study was to investigate the effects of vitamin D deficiency on insuli...

Endometriosis Knowledgebase: a gene-based resource on endometriosis.

Endometriosis is a complex, benign, estrogen-dependent gynecological disorder with an incidence of ~...

Machine Learning Algorithm Helps Identify Non-Diagnosed Prodromal Alzheimer's Disease Patients in the General Population.

BACKGROUND: Recruiting patients for clinical trials of potential therapies for Alzheimer's disease (...

Radiomics with artificial intelligence for precision medicine in radiation therapy.

Recently, the concept of radiomics has emerged from radiation oncology. It is a novel approach for s...

THE ROLE OF E2/P RATIO IN THE ETIOLOGY OF FIBROCYSTIC BREAST DISEASE, MASTALGIA AND MASTODYNIA.

- The aim of the study was to assess the role of the estradiol and progesterone relationship during ...

[Survival Analysis of Stage I Non-small Cell Lung Cancer Patients Treated with 
Da Vinci Robot-assisted Thoracic Surgery].

BACKGROUND: Da Vinci robotic surgery system is widely used in department of thoracic surgery. The ai...

LncRNAnet: long non-coding RNA identification using deep learning.

MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes...

PhotoAgeClock: deep learning algorithms for development of non-invasive visual biomarkers of aging.

Aging biomarkers are the qualitative and quantitative indicators of the aging processes of the human...

Mahalanobis Outier Removal for Improving the Non-Viable Detection on Human Injuries.

Machine learning techniques have been recently applied for discriminating between Viable and Non-Via...

Convolutional neural networks for classification of alignments of non-coding RNA sequences.

MOTIVATION: The convolutional neural network (CNN) has been applied to the classification problem of...

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data.

SUMMARY: We present a web server running the MIIC algorithm, a network learning method combining con...

[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to c...

The New Possibilities from "Big Data" to Overlooked Associations Between Diabetes, Biochemical Parameters, Glucose Control, and Osteoporosis.

PURPOSE OF REVIEW: To review current practices and technologies within the scope of "Big Data" that ...

Effect of the Synchronization-Based Control of a Wearable Robot Having a Non-Exoskeletal Structure on the Hemiplegic Gait of Stroke Patients.

We have been developing the robotic wear curara as both a welfare device and rehabilitation robot th...

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