Latest AI and machine learning research in endocrinology for healthcare professionals.
AIMS: Early identification of pharmacological therapy for gestational diabetes mellitus (GDM), a common pregnancy complication, through machine learning could allow for better therapeutic strategies and improved treatment efficiency. This scoping review aimed to comprehensively review the machine learning models used to predict the need for pharmacological therapy in GDM. METHODS: Four electronic ...
PURPOSE: Pediatric adrenocortical tumors (pACTs) are rare and clinically heterogeneous. Existing risk stratification systems rely on fixed thresholds and linear assumptions, which may limit their prognostic accuracy-particularly for nonmetastatic, locally advanced cases. We aimed to develop an interpretable machine learning (ML) model for individualized survival prediction using only routine clini...
AIMS/HYPOTHESIS: Available methods for predicting the onset and progression of diabetic kidney disease (DKD) and end-stage kidney disease (ESKD) are n...
The use of artificial intelligence (AI) to improve the diagnosis, assessment and treatment of people with diabetes has the potential to drive a paradi...
OBJECTIVES: Thyroid nodules are one of the most common thyroid disorders and can be categorized into benign and malignant thyroid nodules. Currently, ...
KEY POINTS: Artificial intelligence models effectively generalized across studies and animal models and reduced translational gaps when applied to hum...
Postprandial hyperglycemia is a key driver in the development of type 2 diabetes, and dietary starch is a major modulator of glycemic response. The cr...
AIMS/HYPOTHESIS: This study aimed to compare the predictive performance of HbA1c and a continuous glucose monitoring (CGM)-based updated glucose manag...
PURPOSE OF REVIEW: Noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP) has been recognized as a diagnostic entity sin...
Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hype...
AIM: To develop and validate models that use electronic health record (EHR) data to predict diabetic ketoacidosis (DKA)-related hospitalizations over ...
PURPOSE: Glucose homeostasis relies on coordinated interactions among multiple organs, and its disruption relates to diabetes development. This study ...
BACKGROUND: Urinary tract infection (UTI) is a serious problem in the healthcare system. It is caused by bacteria from the gastrointestinal tract. The...
PURPOSE OF REVIEW: Diabetes foot ulcers (DFUs) affect millions globally, and are a global health challenge, contributing significantly to morbidity, m...
BACKGROUND: Lymph node metastasis (LNM) is a critical prognostic indicator in papillary thyroid carcinoma (PTC), significantly influencing surgical de...
Biomarker research in psychopathology increasingly employs high-dimensional Omics approaches. Yet, proteomics based on human hair remain largely unexp...
Gut microbiome (GME) is a dynamic ecosystem composed of diverse microorganisms with extensive functional potential that influence host physiology, end...
UNLABELLED: This article presents the design, implementation, and evaluation of MarIA, a GPT-3.5-powered virtual assistant integrated into a messaging...
The relationship between Gestational Diabetes Mellitus (GDM) and Retinopathy of Prematurity (ROP) is not fully understood, but both conditions may sha...
BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi...