Endocrinology

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges.

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial economic burden make diabetes a significant health challenge worldwide. A shortage of diabetes specialists, uneven distribution of medical resources, low adherence to medications, and improper self-management contribute to poor glycemic control in patien...

An effective correlation-based data modeling framework for automatic diabetes prediction using machine and deep learning techniques.

The rising risk of diabetes, particularly in emerging countries, highlights the importance of early detection. Manual prediction can be a challenging task, leading to the need for automatic approaches. The major challenge with biomedical datasets is data scarcity. Biomedical data is often difficult to obtain in large quantities, which can limit the ability to train deep learning models effectively...

Immune response and mesenchymal transition of papillary thyroid carcinoma reflected in ultrasonography features assessed by radiologists and deep learning.

INTRODUCTION: Ultrasonography (US) features of papillary thyroid cancers (PTCs) are used to select nodules for biopsy due to their association with tu...

TumorDetNet: A unified deep learning model for brain tumor detection and classification.

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of p...

A Graph Neural Network Model with a Transparent Decision-Making Process Defines the Applicability Domain for Environmental Estrogen Screening.

The application of deep learning (DL) models for screening environmental estrogens (EEs) for the sound management of chemicals has garnered significan...

Osteoporosis in Adrenal Insufficiency: Could Metformin be Protective?

Adrenal insufficiency (AI) is a serious disorder characterized by the adrenal glucocorticoid deficiency. Regardless of the etiology, AI patients need ...

Diagnosis of diabetes mellitus using high frequency ultrasound and convolutional neural network.

The incidence of diabetes mellitus has been increasing, prompting the search for non-invasive diagnostic methods. Although current methods exist, thes...

Application of serum SERS technology combined with deep learning algorithm in the rapid diagnosis of immune diseases and chronic kidney disease.

Surface-enhanced Raman spectroscopy (SERS), as a rapid, non-invasive and reliable spectroscopic detection technique, has promising applications in dis...

Can artificial intelligence replace biochemists? A study comparing interpretation of thyroid function test results by ChatGPT and Google Bard to practising biochemists.

BACKGROUND: Public awareness of artificial intelligence (AI) is increasing and this novel technology is being used for a range of everyday tasks and m...

Application of machine learning and artificial intelligence in the diagnosis and classification of polycystic ovarian syndrome: a systematic review.

INTRODUCTION: Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed lead...

As artificial intelligence goes multimodal, medical applications multiply.

Machines don't have eyes, but you wouldn't know that if you followed the progression of deep learning models for accurate interpretation of medical im...

Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.

AIMS: The International Medullary Thyroid Carcinoma Grading System, introduced in 2022, mandates evaluation of the Ki67 proliferation index to assign ...

A study on the appropriate dose of rocuronium for intraoperative neuromonitoring in Da Vinci robot thyroid surgery: a randomized, double-blind, controlled trial.

BACKGROUND: This study was to explore the effect of different doses of rocuronium bromide on neuromonitoring during Da Vinci robot thyroid surgery.

Deep Transfer Learning-Based Approach for Glucose Transporter-1 (GLUT1) Expression Assessment.

Glucose transporter-1 (GLUT-1) expression level is a biomarker of tumour hypoxia condition in immunohistochemistry (IHC)-stained images. Thus, the GLU...

Insulin-Induced Lipohypertrophy Treated With Liposuction: A Review of Case Reports.

Lipohypertrophy is the most reported cutaneous complication of insulin injection. In cases refractory to conservative management, liposuction has bee...

Value of Artificial Intelligence in Improving the Accuracy of Diagnosing TI-RADS Category 4 Nodules.

OBJECTIVE: Considerable heterogeneity is observed in the malignancy rates of thyroid nodules classified as category 4 according to the Thyroid Imaging...

Can ChatGPT Help in the Awareness of Diabetes?

Diabetes is a common chronic illness that requires continual patient education and support to be effectively managed. The lack of diabetes educators a...

Diabetic Retinopathy Screening Using Smartphone-Based Fundus Photography and Deep-Learning Artificial Intelligence in the Yucatan Peninsula: A Field Study.

BACKGROUND: To compare the performance of Medios (offline) and EyeArt (online) artificial intelligence (AI) algorithms for detecting diabetic retinopa...

Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiot...

Prediction of central lymph node metastasis based on deep learning models for patients with clinically node-negative papillary thyroid carcinoma.