Endocrinology

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

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Showing 169-189 of 4,956 articles
In-silico guided identification and studies of potential FFAR4 agonists for type 2 diabetes mellitus therapy.

BACKGROUND: The activation of free fatty acid receptor 4 (FFAR4) enhances insulin sensitivity and gl...

Utilization of artificial intelligence in Men's Health: Opportunities for innovation and quality improvement.

Artificial intelligence (AI) is reshaping the landscape of men's health by enhancing diagnostic accu...

Classification of Diabetic Patients using a Network Representation of Their Metabolism.

Studies on Type 2 Diabetes Mellitus (T2DM) rely on specific metabolic networks to represent the intr...

3Mont: A multi-omics integrative tool for breast cancer subtype stratification.

Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types am...

Integrative Machine Learning Approach for Predicting Resistance to First-Generation Receptor Ligands in Acromegaly.

CONTEXT: Acromegaly, caused by excess growth hormone (GH) and insulin-like growth factor-1 (IGF-1) d...

Aptamer-directed siRNA delivery systems for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the ...

Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology.

BACKGROUND: Brominated flame retardants (BFRs) are classified as important endocrine disruptors and ...

Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction.

Precise forecasting of cancer outcomes is essential for medical professionals to assess the well-bei...

Application of IRSA-BP neural network in diagnosing diabetes.

Within the healthcare sector, the application of machine learning is gaining prominence, notably enh...

Big data and cardiovascular risk-insights into obesity, diabetes, and coronary heart disease.

BACKGROUND: Cardiovascular diseases (CVD) remain a major global health burden. Obesity and type 2 di...

Interpretable machine learning insights into the association between PFAS exposure and diabetes mellitus.

BACKGROUND: Diabetes Mellitus (DM) is a global health concern with rising prevalence, and its link t...

Ensemble-based Convolutional Neural Networks for brain tumor classification in MRI: Enhancing accuracy and interpretability using explainable AI.

BACKGROUND: Accurate and efficient classification of brain tumors, including gliomas, meningiomas, a...

Effectiveness and safety of AI-driven closed-loop systems in diabetes management: a systematic review and meta-analysis.

BACKGROUND: Diabetes is a metabolic disease that can lead to severe cardiovascular diseases and neur...

Association rule mining of the human gut microbiome.

The human gut carries a vast and diverse microbial community that is essential for human health. Und...

Artificial intelligence in polycystic ovarian syndrome management: past, present, and future.

BACKGROUND: Integrating artificial intelligence (AI) prospected in the practical clinical management...

Machine learning-based QSAR and molecular modeling identify promising PTP1B modulators from Ocimum gratissimum for type 2 diabetes therapy.

Protein tyrosine phosphatase 1B (PTP1B) is a key negative regulator of insulin signaling and a promi...

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