Endocrinology

A Deep Learning Framework for Earlier Prediction of Diabetic Retinopathy from Fundus Photographs.

Diabetic patients can also be identified immediately utilizing retinopathy photos, but it is a challenging task. The blood veins visible in fundus photographs are used in several disease diagnosis approaches. We sought to replicate the findings published in implementation and verification of a deep learning approach for diabetic retinopathy identification in retinal fundus pictures. To address thi...

Conversion rates in robotic thyroid surgery: A systematic review and meta-analysis.

OBJECTIVE: To define the conversion risk to open procedure during robot-assisted thyroid surgery (RATS) identifying potential specific subclasses of procedures or accesses at higher conversion risk.

Simulating the restoration of normal gene expression from different thyroid cancer stages using deep learning.

BACKGROUND: Thyroid cancer (THCA) is the most common endocrine malignancy and incidence is increasing. There is an urgent need to better understand th...

Symmetric Convolutional and Adversarial Neural Network Enables Improved Mental Stress Classification From EEG.

Electroencephalography (EEG) is widely used for mental stress classification, but effective feature extraction and transfer across subjects remain cha...

Robot assisted laparoscopic adrenalectomy: Should this be the new standard?

INTRODUCTION: Minimal invasive surgeries (MIS) for large size adrenal tumors are still debatable. The objective is to evaluate the contemporary peri- ...

Identification and epidemiological characterization of Type-2 diabetes sub-population using an unsupervised machine learning approach.

BACKGROUND: Studies on Type-2 Diabetes Mellitus (T2DM) have revealed heterogeneous sub-populations in terms of underlying pathologies. However, the id...

Fear Detection in Multimodal Affective Computing: Physiological Signals versus Catecholamine Concentration.

Affective computing through physiological signals monitoring is currently a hot topic in the scientific literature, but also in the industry. Many wea...

Enhancement of Detection of Diabetic Retinopathy Using Harris Hawks Optimization with Deep Learning Model.

In today's world, diabetic retinopathy is a very severe health issue, which is affecting many humans of different age groups. Due to the high levels o...

Feature discretization-based deep clustering for thyroid ultrasound image feature extraction.

Ultrasound imaging technology has the advantage of being convenient, less harmful and widely applied, making ultrasonography one of the most popular m...

Classification of Thyroid Nodules by Using Deep Learning Radiomics Based on Ultrasound Dynamic Video.

OBJECTIVES: We aimed to design a radiomics model for differential diagnosis of thyroid carcinoma based on dynamic ultrasound video, and compare its di...

Patient Benefit and Quality of Life after Robot-Assisted Head and Neck Surgery.

Robotic systems for head and neck surgery are at different stages of technical development and clinical application. Currently, robotic systems are pr...

Diagnostic accuracy of code-free deep learning for detection and evaluation of posterior capsule opacification.

OBJECTIVE: To train and validate a code-free deep learning system (CFDLS) on classifying high-resolution digital retroillumination images of posterior...

Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study.

OBJECTIVES: Ki67 is an important biomarker of pituitary adenoma (PA) aggressiveness. In this study, PA invasion of surrounding structures is investiga...

A large intrathoracic goiter with tracheal stenosis: Complete resection using a robot-assisted thoracoscopic approach.

Growing intrathoracic goiters may compress surrounding organs and deteriorate the cardiopulmonary function. Treating such cases requires carefully con...

A computer-aided diagnosis system for detecting various diabetic retinopathy grades based on a hybrid deep learning technique.

Diabetic retinopathy (DR) is a serious disease that may cause vision loss unawares without any alarm. Therefore, it is essential to scan and audit the...

A deep learning-based approach for the diagnosis of adrenal adenoma: a new trial using CT.

OBJECTIVE: To develop and validate deep convolutional neural network (DCNN) models for the diagnosis of adrenal adenoma (AA) using CT.

Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.

PURPOSE: Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence tomography (OCT) images. We aimed to evaluate the...

Dietary administration of D-chiro-inositol attenuates sex-specific metabolic imbalances in the 5xFAD mouse model of Alzheimer's disease.

Increasing evidence shows that hypothalamic dysfunction, insulin resistance, and weight loss precede and progress along with the cognitive decline in ...

Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.

Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obese individuals. Physical exercise is an important e...

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T.

To evaluate the clinical performance of a deep learning-accelerated single-breath-hold half-Fourier acquisition single-shot turbo spin echo (HASTE)-se...