Endocrinology

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

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Objective assessment of segmentation models for thyroid ultrasound images.

Ultrasound features related to thyroid lesions structure, shape, volume, and margins are considered ...

Prevalence and Early Prediction of Diabetes Using Machine Learning in North Kashmir: A Case Study of District Bandipora.

Diabetes is one of the biggest health problems that affect millions of people across the world. Unco...

Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model.

Management of diabetes requires a multifaceted approach of risk factor reduction; through management...

Robot-assisted vs laparoscopic lateral transabdominal adrenalectomy: a propensity score matching analysis.

BACKGROUND: Laparoscopic adrenalectomy (LA) is the gold standard treatment for adrenal lesions. Robo...

Detecting High-Risk Factors and Early Diagnosis of Diabetes Using Machine Learning Methods.

Diabetes is a chronic disease that can cause several forms of chronic damage to the human body, incl...

Early Prediction of Diabetes Using an Ensemble of Machine Learning Models.

Diabetes is one of the most rapidly spreading diseases in the world, resulting in an array of signif...

Temporal deep learning framework for retinopathy prediction in patients with type 1 diabetes.

The adoption of electronic health records in hospitals has ensured the availability of large dataset...

Artificial intelligence in adrenal imaging: A critical review of current applications.

In the elective field of adrenal imaging, artificial intelligence (AI) can be used for adrenal lesio...

Machine Learning for Adrenal Gland Segmentation and Classification of Normal and Adrenal Masses at CT.

Background Adrenal masses are common, but radiology reporting and recommendations for management can...

A Prediction Algorithm for Hypoglycemia Based on Support Vector Machine Using Glucose Level and Electrocardiogram.

A prediction algorithm for hypoglycemic events is proposed using glucose levels and electrocardiogra...

Minimized Computations of Deep Learning Technique for Early Diagnosis of Diabetic Retinopathy Using IoT-Based Medical Devices.

Diabetes mellitus is the main cause of diabetic retinopathy, the most common cause of blindness worl...

Identifying Glucose Metabolism Status in Nondiabetic Japanese Adults Using Machine Learning Model with Simple Questionnaire.

We aimed to identify the glucose metabolism statuses of nondiabetic Japanese adults using a machine ...

Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions.

Deep learning (DL) enables the creation of computational models comprising multiple processing layer...

Is handling unbalanced datasets for machine learning uplifts system performance?: A case of diabetic prediction.

BACKGROUND AND AIMS: Healthcare is a sensitive sector, and addressing the class imbalance in the hea...

Regulation of Quality of Life and Immune Function in Patients with Thyroid Cancer Treated by Deep Learning Technology.

BACKGROUND: In order to explore the regulation of quality of life and immune function in patients wi...

Machine learning-assisted discovery of growth decision elements by relating bacterial population dynamics to environmental diversity.

Microorganisms growing in their habitat constitute a complex system. How the individual constituents...

Novel Internet of Things based approach toward diabetes prediction using deep learning models.

The integration of the Internet of Things with machine learning in different disciplines has benefit...

Modeling biosurfactant production from agroindustrial residues by neural networks and polynomial models adjusted by particle swarm optimization.

Biosurfactants are molecules with wide application in several industrial processes. Their production...

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