Endocrinology

Automatic differentiation of thyroid scintigram by deep convolutional neural network: a dual center study.

BACKGROUND: Tc-pertechnetate thyroid scintigraphy is a valid complementary avenue for evaluating thyroid disease in the clinic, the image feature of thyroid scintigram is relatively simple but the interpretation still has a moderate consistency among physicians. Thus, we aimed to develop an artificial intelligence (AI) system to automatically classify the four patterns of thyroid scintigram.

Phytogenic compounds from avocado ( L.) extracts; antioxidant activity, amylase inhibitory activity, therapeutic potential of type 2 diabetes.

Diabetes is a worldwide public health disease. Currently, the most effective way to treat diabetes is to mitigate postprandial hyperglycemia by inhibiting carbohydrate hydrolysis enzymes in the digestive system. Plant extracts are rich in bioactive compounds, which can be used in diabetes treatment. This study aims to evaluate the polyphenols content in ethanolic extracts of avocado fruit and leav...

Positive effects of thyroid replacement therapy on assisted reproductive technology outcomes in women with subclinical hypothyroidism with positive thyroid peroxidase autoantibodies.

OBJECTIVE: To study the beneficial effects of thyroid replacement therapy (TRT) on pregnancy outcomes in patients with subclinical hypothyroidism (SCl...

Thyroglobulin Levels in Patients who have Undergone Hemithyroidectomy for Differentiated Thyroid Cancer. An Assessment of Levels and Trends at a Tertiary Referral Centre.

Subramanian Kannan Serum thyroglobulin (Tg) and thyroglobulin antibody (TgAb) levels are used to monitor patients with differentiated thyroid cancer (...

90% Accuracy for Photoplethysmography-Based Non-Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c.

Previously published photoplethysmography-(PPG) based non-invasive blood glucose (NIBG) measurements have not yet been validated over 500 subjects. As...

Machine Learning-Based Gynecologic Tumor Diagnosis and Its Postoperative Incisional Infection Influence Factor Analysis.

Various factors influencing postoperative incisional infection in gynecologic tumors were analyzed, and the value of quality nursing intervention was ...

Adrenal Insufficiency in Septic Patients Admitted to Intensive Care Unit: Prevalence and Associated Factors.

Adrenal insufficiency (AI) is associated with an increase in the risk of mortality in ICU-admitted septic patients. It should be suspected not only i...

The Long-Term Effect of Intensity Modulated Radiation Therapy for Prostate Cancer on Testosterone Levels.

PURPOSE: Concern about a long-term effect of the delivery of intensity modulated radiation therapy (IMRT) for prostate cancer on serum testosterone le...

A deep learning-based method for detecting and classifying the ultrasound images of suspicious thyroid nodules.

PURPOSE: The incidence of thyroid cancer has significantly increased in the last few decades. However, diagnosis of the thyroid nodules is labor and t...

mHealth apps for gestational diabetes mellitus that provide clinical decision support or artificial intelligence: A scoping review.

AIMS: Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. M...

Emulating complex simulations by machine learning methods.

BACKGROUND: The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More ...

Prognostic biomarkers for predicting papillary thyroid carcinoma patients at high risk using nine genes of apoptotic pathway.

Aberrant expressions of apoptotic genes have been associated with papillary thyroid carcinoma (PTC) in the past, however, their prognostic role and ut...

Machine intelligence in non-invasive endocrine cancer diagnostics.

Artificial intelligence (AI) has illuminated a clear path towards an evolving health-care system replete with enhanced precision and computing capabil...

Racial/ethnic and socioeconomic disparities in the use of newer diabetes medications in the Look AHEAD study.

BACKGROUND: Among patients with type 2 diabetes, minority racial/ethnic groups have a higher burden of cardiovascular disease, chronic kidney disease,...

Detection of diabetes from whole-body MRI using deep learning.

Obesity is one of the main drivers of type 2 diabetes, but it is not uniformly associated with the disease. The location of fat accumulation is critic...

General deep learning model for detecting diabetic retinopathy.

BACKGROUND: Doctors can detect symptoms of diabetic retinopathy (DR) early by using retinal ophthalmoscopy, and they can improve diagnostic efficiency...

Single-port transaxillary robotic thyroidectomy (START): 200-cases with two-step retraction method.

BACKGROUND: This study aims to report the results of a pioneering clinical study using the single-port transaxillary robotic thyroidectomy (START) for...

[Type 1 diabetes mellitus and Graves Basedow's disease, a case of Autoimmune Polyglandular Syndrome].

INTRODUCTION: Type 1 diabetes mellitus (T1DM) is one of the most frequent autoimmune diseases in childhood. Its diagnosis requires the search for othe...

Improvement of the Force Field for -d-Glucose with Machine Learning.

While the construction of a dependable force field for performing classical molecular dynamics (MD) simulation is crucial for elucidating the structur...

Pivotal Evaluation of an Artificial Intelligence System for Autonomous Detection of Referrable and Vision-Threatening Diabetic Retinopathy.

IMPORTANCE: Diabetic retinopathy (DR) is a leading cause of blindness in adults worldwide. Early detection and intervention can prevent blindness; how...