Endocrinology

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 with thyroid cancer after radiotherapy, a method based on deep learning technology was proposed. A deep learning detection method for thyroid cancer is proposed.

Deep Learning Classification of Treatment Response in Diabetic Painful Neuropathy: A Combined Machine Learning and Magnetic Resonance Neuroimaging Methodological Study.

Functional magnetic resonance imaging (fMRI) has been shown successfully to assess and stratify patients with painful diabetic peripheral neuropathy (pDPN). This supports the idea of using neuroimaging as a mechanism-based technique to individualise therapy for patients with painful DPN. The aim of this study was to use deep learning to predict treatment response in patients with pDPN using restin...

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 of the environment contribute to microbial growth...

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 benefited from recent technological advancements. In medi...

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 is damaged due to inefficient bioprocessing and e...

Diabetic retinopathy screening using deep learning for multi-class imbalanced datasets.

Screening and diagnosis of diabetic retinopathy disease is a well known problem in the biomedical domain. The use of medical imagery from a patient's ...

Deep learning fuzzy immersion and invariance control for type-I diabetes.

In this study, a novel approach is proposed for glucose regulation in type-I diabetes patients. Unlike most studies, the glucose-insulin metabolism is...

Feasibility Study of Constructing a Screening Tool for Adolescent Diabetes Detection Applying Machine Learning Methods.

Prediabetes and diabetes are becoming alarmingly prevalent among adolescents over the past decade. However, an effective screening tool that can asses...

Liver enzymes, alcohol consumption and the risk of diabetes: the Suita study.

AIM: We aimed to investigate the combined impact of liver enzymes and alcohol consumption on the diabetes risk.

Characterization of the SGLT2 Interaction Network and Its Regulation by SGLT2 Inhibitors: A Bioinformatic Analysis.

Sodium-glucose cotransporter 2 (SGLT2), also known as solute carrier family 5 member 2 (SLC5A2), is a promising target for a new class of drugs prima...

Multi-Modal Brain Tumor Detection Using Deep Neural Network and Multiclass SVM.

Clinical diagnosis has become very significant in today's health system. The most serious disease and the leading cause of mortality globally is brai...

A Deep Learning Model Incorporating Knowledge Representation Vectors and Its Application in Diabetes Prediction.

The deep learning methods for various disease prediction tasks have become very effective and even surpass human experts. However, the lack of interpr...

Predicting difficult airway intubation in thyroid surgery using multiple machine learning and deep learning algorithms.

BACKGROUND: In this paper, we examine whether machine learning and deep learning can be used to predict difficult airway intubation in patients underg...

Deep multi-scale resemblance network for the sub-class differentiation of adrenal masses on computed tomography images.

OBJECTIVE: The accurate classification of mass lesions in the adrenal glands ('adrenal masses'), detected with computed tomography (CT), is important ...

A deep learning-based algorithm for tall cell detection in papillary thyroid carcinoma.

INTRODUCTION: According to the World Health Organization, the tall cell variant (TCV) is an aggressive subtype of papillary thyroid carcinoma (PTC) co...

A comprehensive review of methods based on deep learning for diabetes-related foot ulcers.

BACKGROUND: Diabetes mellitus (DM) is a chronic disease with hyperglycemia. If not treated in time, it may lead to lower limb amputation. At the initi...

Integrated biomarker approach strongly explaining in vivo sub-lethal acute toxicity of butachlor on Labeo rohita.

Butachlor herbicide belongs to the family of chloroacetanilide group, widely used for control of grass and broadleaf weeds in paddy fields however, it...

Optimization assisted framework for thyroid detection and classification: A new ensemble technique.

Ultrasound (US) is an inexpensive and non-invasive technique for capturing the image of the thyroid gland and nearby tissue. The classification and de...

Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework.

OBJECTIVE: As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood f...

Gray wolf optimization-extreme learning machine approach for diabetic retinopathy detection.

Many works have employed Machine Learning (ML) techniques in the detection of Diabetic Retinopathy (DR), a disease that affects the human eye. However...