AI Medical Compendium Journal:
Journal of endocrinological investigation

Showing 1 to 5 of 5 articles

Longitudinal changes in minerals are influenced by immunosuppressive treatment in men with granuloma disease.

Journal of endocrinological investigation
PURPOSE: To investigate whether granuloma formation following self-administered cosmetic oil injections affects mineral homeostasis, specifically calcium, magnesium, phosphate, iron, sodium, and potassium, and to assess the potential impact of predni...

Enhancing gestational diabetes mellitus risk assessment and treatment through GDMPredictor: a machine learning approach.

Journal of endocrinological investigation
BACKGROUND: Gestational diabetes mellitus (GDM) is a serious health concern that affects pregnant women worldwide and can lead to adverse pregnancy outcomes. Early detection of high-risk individuals and the implementation of appropriate treatment can...

A machine learning model to predict therapeutic inertia in type 2 diabetes using electronic health record data.

Journal of endocrinological investigation
OBJECTIVE: To estimate the therapeutic inertia prevalence for patients with type 2 diabetes, develop and validate a machine learning model predicting therapeutic inertia, and determine the added predictive value of area-level social determinants of h...

Artificial intelligence in endocrinology: a comprehensive review.

Journal of endocrinological investigation
BACKGROUND AND AIM: Artificial intelligence (AI) has emerged as a promising technology in the field of endocrinology, offering significant potential to revolutionize the diagnosis, treatment, and management of endocrine disorders. This comprehensive ...

Polycystic ovary syndrome: clinical and laboratory variables related to new phenotypes using machine-learning models.

Journal of endocrinological investigation
PURPOSE: Polycystic Ovary Syndrome (PCOS) is the most frequent endocrinopathy in women of reproductive age. Machine learning (ML) is the area of artificial intelligence with a focus on predictive computing algorithms. We aimed to define the most rele...