Endocrinology

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

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Beyond genomics: artificial intelligence-powered diagnostics for indeterminate thyroid nodules-a systematic review and meta-analysis.

INTRODUCTION: In recent years, artificial intelligence (AI) tools have become widely studied for thy...

Leveraging AI to explore structural contexts of post-translational modifications in drug binding.

Post-translational modifications (PTMs) play a crucial role in allowing cells to expand the function...

Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.

OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tube...

Multimodal GPT model for assisting thyroid nodule diagnosis and management.

Although using artificial intelligence (AI) to analyze ultrasound images is a promising approach to ...

Development of an activity-based ratiometric electrochemical substrate for measuring circulating dipeptidyl peptidase-IV/CD26 in whole blood samples.

Dipeptidyl peptidase-IV (DPP-IV) is a circulating blood biomarker that diagnose pancreatic and thyro...

Comprehensive analysis of Syzygium cumini L. pomace extract as an α-amylase inhibitor: In vitro inhibition, kinetics, and computational studies.

Type 2 diabetes mellitus (T2DM) is a widespread metabolic disorder characterized by impaired regulat...

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study.

This research letter presents a cross-sectional analysis comparing the agreement between artificial ...

A cascade nanoreactor based on metal azolate framework integrated natural enzyme for α-glucosidase activity assay and inhibitor screening.

Enzyme cascades have attracted widespread attention owing to the exceptional specificity and efficie...

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for a...

Machine learning based identification of anoikis related gene classification patterns and immunoinfiltration characteristics in diabetic nephropathy.

Anoikis and immune cell infiltration are pivotal factors in the pathophysiological mechanism of diab...

Advancement in early diagnosis of polycystic ovary syndrome: biomarker-driven innovative diagnostic sensor.

Polycystic ovary syndrome (PCOS) is a heterogeneous multifactorial endocrine disorder that affects o...

GBE1 alleviates MPTP-induced PD symptoms in mice by enhancing glycolysis and oxidative phosphorylation.

In Parkinson's disease (PD), the disturbance of energy metabolism due to glucose metabolic reprogram...

Insulin resistance in type 1 diabetes is a key modulator of platelet hyperreactivity.

AIMS/HYPOTHESIS: Individuals with type 1 diabetes are at increased cardiovascular risk, particularly...

From Nuclear Receptors to GPCRs: a Deep Transfer Learning Approach for Enhanced Environmental Estrogen Recognition.

Environmental estrogens (EEs), as typical endocrine-disrupting chemicals (EDCs), can bind to classic...

A hybrid deep learning framework for early detection of diabetic retinopathy using retinal fundus images.

Recent advancements in deep learning have significantly impacted medical image processing domain, en...

Machine Learning-Driven Identification of Hematological and Immunological Biomarkers for Predicting Proliferative Diabetic Retinopathy Progression.

PURPOSE: Proliferative Diabetic Retinopathy (PDR) is a severe complication of diabetes characterized...

ConsisTNet: a spatio-temporal approach for consistent anatomical localization in endoscopic pituitary surgery.

PURPOSE: Automated localization of critical anatomical structures in endoscopic pituitary surgery is...

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.

BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and d...

Brain tumor detection empowered with ensemble deep learning approaches from MRI scan images.

Brain tumor detection is essential for early diagnosis and successful treatment, both of which can s...

Construction of a Multimodal Machine Learning Model for Papillary Thyroid Carcinoma Based on Pathomics and Ultrasound Radiomics Dataset.

The use of machine learning to integrate and analyse multimodal information has broad prospects for ...

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