AI Medical Compendium Journal:
Frontiers in endocrinology

Showing 1 to 10 of 141 articles

Machine learning-based coronary heart disease diagnosis model for type 2 diabetes patients.

Frontiers in endocrinology
BACKGROUND: To establish a classification model for assisting the diagnosis of type 2 diabetes mellitus (T2DM) complicated with coronary heart disease (CHD).

Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification.

Frontiers in endocrinology
OBJECTIVE: Accurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. Indeterminate thyroid nodules (ITNs) ...

Predicting central lymph node metastasis in papillary thyroid microcarcinoma: a breakthrough with interpretable machine learning.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an interpretable machine learning (ML) model for the preoperative prediction of central lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC).

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

Frontiers in endocrinology
INTRODUCTION: In recent years, artificial intelligence (AI) tools have become widely studied for thyroid ultrasonography (USG) classification. The real-world applicability of these developed tools as pre-operative diagnostic aids is limited due to mo...

Predicting isolated impaired glucose tolerance without oral glucose tolerance test using machine learning in Chinese Han men.

Frontiers in endocrinology
BACKGROUND: Isolated Impaired Glucose Tolerance (I-IGT) represents a specific prediabetic state that typically requires a standardized oral glucose tolerance test (OGTT) for diagnosis. This study aims to predict glucose tolerance status in Chinese Ha...

Comparison of artificial intelligence-generated and physician-generated patient education materials on early diabetic kidney disease.

Frontiers in endocrinology
BACKGROUND: Diabetic kidney disease (DKD) is a common and serious complication of diabetes mellitus and has become the most important cause of end-stage renal disease (ESRD). In light of the rising prevalence of diabetes, there is a growing imperativ...

Optimizing predictive features using machine learning for early miscarriage risk following single vitrified-warmed blastocyst transfer.

Frontiers in endocrinology
RESEARCH QUESTION: Can machine learning models accurately predict the risk of early miscarriage following single vitrified-warmed blastocyst transfer (SVBT)?

TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models.

Frontiers in endocrinology
BACKGROUND: Prostate cancer (PCa) in the transition zone (TZ) is uncommon and often poses challenges for early diagnosis, but its genomic determinants and therapeutic vulnerabilities remain poorly characterized.

Construction and validation of a deep learning-based diagnostic model for segmentation and classification of diabetic foot.

Frontiers in endocrinology
OBJECTIVE: This study aims to conduct an in-depth analysis of diabetic foot ulcer (DFU) images using deep learning models, achieving automated segmentation and classification of the wounds, with the goal of exploring the application of artificial int...

Cardiometabolic index predicts cardiovascular events in aging population: a machine learning-based risk prediction framework from a large-scale longitudinal study.

Frontiers in endocrinology
BACKGROUND: While the Cardiometabolic Index (CMI) serves as a novel marker for assessing adipose tissue distribution and metabolic function, its prognostic utility for cardiovascular disease (CVD) events remains incompletely understood. This investig...