Endocrinology

Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets.

Diabetes Mellitus (DM) is a global health challenge, and accurate early detection is critical for effective management. The study explores the potential of machine learning for improved diabetes prediction using microarray gene expression data and PIMA data set. Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) follow...

GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series.

Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with type 1 or 2 diabetes, thereby reducing complications and improving quality of life. The state of the art of BG prediction has been achieved by leveraging advanced deep learning methods to model multimodal data, i.e., sensor data and self-reported event data, organized as multi-varia...

REMED-T2D: A robust ensemble learning model for early detection of type 2 diabetes using healthcare dataset.

Early diagnosis and timely treatment of diabetes are critical for effective disease management and the prevention of complications. Undiagnosed diabet...

Estimation of Hematocrit Volume Using Blood Glucose Concentration through Extreme Gradient Boosting Regressor Machine Learning Model.

Lifestyle diseases such as cardiovascular disorders, diabetes, etc. affect the physiological metabolism and become chronic upon negligence. Diabetes i...

Demystifying Infusion Pumps: Design of a Cost-Effective Platform for Education and Innovation.

INTRODUCTION: This article presents a cost-effective, modular infusion platform to help diabetes specialists customize and understand infusion pump me...

Identification of biomarkers associated with macrophage polarization in diabetic cardiomyopathy based on bioinformatics and machine learning approaches.

BACKGROUND: Numerous studies have investigated the role of macrophages in the pathogenesis of diabetic cardiomyopathy (DCM); however, the underlying m...

ThyroNet-X4 genesis: an advanced deep learning model for auxiliary diagnosis of thyroid nodules' malignancy.

Thyroid nodules are a common endocrine condition, and accurate differentiation between benign and malignant nodules is essential for making appropriat...

[Use of Artificial Intelligence in Diabetic Retinopathy Screening: Experience in a Health Service in Santiago, Chile].

UNLABELLED: Early detection of diabetic retinopathy is critical for preventing vision loss.

Conventional and machine learning-based analysis of age, body weight and body height significance in knot position-related thyrohyoid and cervical spine fractures in suicidal hangings.

The thyrohyoid complex and cervical spine fracture distribution patterns may reflect the knot position as the force distribution by the noose to diffe...

Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.

Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical to...

Optimal selection of diagnostic method for diabetes mellitus using complex bipolar fuzzy dynamic data.

Diabetes mellitus refers to a collection of metabolic disorders that affect the way carbohydrates are processed in the body. It is a prominent worldwi...

Optimizing hypoglycaemia prediction in type 1 diabetes with Ensemble Machine Learning modeling.

BACKGROUND: Type 1 diabetes (T1D) is a chronic endocrine disorder characterized by high blood glucose levels, impacting millions of people globally. I...

Autonomous Screening for Diabetic Macular Edema Using Deep Learning Processing of Retinal Images.

OBJECTIVE: To develop and validate a deep learning model for diabetic macular edema (DME) detection using color fundus imaging, which is applicable in...

Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared...

Risk factor assessment of prediabetes and diabetes based on epidemic characteristics in new urban areas: a retrospective and a machine learning study.

To explore in depth the characteristics of the risk factors for diabetes and prediabetes pathogenesis and progression in special regions. We investiga...

Secretary bird optimization algorithm based on quantum computing and multiple strategies improvement for KELM diabetes classification.

The classification of chronic diseases has long been a prominent research focus in the field of public health, with widespread application of machine ...

A deep learning based model for diabetic retinopathy grading.

Diabetic retinopathy stands as a leading cause of blindness among people. Manual examination of DR images is labor-intensive and prone to error. Exist...

Ultrasound and histopathological assessment of benign, borderline, and malignant thyroid tumors in pediatric patients: an illustrative review and literature overview.

BACKGROUND: The risk of malignancy in thyroid nodules is higher in children than in adults, often necessitating a more aggressive endocrine and surgic...

Paradigms of intraoperative neuromonitoring in paediatric thyroid surgery.

The larynx of children and adolescents is still in the developmental phase and the anatomical structure is still very small and sensitive. The higher ...

A Prospective Pilot Study Demonstrating Noninvasive Calibration-Free Glucose Measurement.

BACKGROUND: Glucose is an essential molecule in energy metabolism. Dysregulated glucose metabolism, the defining feature of diabetes, requires active ...