Endocrinology

Development of a machine learning model for predicting cardiovascular risk factors and major adverse cardiovascular events in young adults with glucose metabolism disorders.

BACKGROUND: Glucose metabolism disorders (GMDs) are a serious global public health issue, characteri...

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania.

Tanzania has the highest age-adjusted prevalence of diabetes in sub-Saharan Africa. Diabetic retinop...

Machine Learning Insights Into Amputation Risk: Evaluating Wound Classification Systems in Diabetic Foot Ulcers.

This study compares the performance of various wound classification systems to determine which syste...

CGMformer: a novel deep-learning model promising for early detection of prediabetes to effectively prevent type 2 diabetes.

Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.

Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and inf...

Vision transformer-based stratification of pre/diabetic and pre/hypertensive patients from retinal photographs for 3PM applications.

OBJECTIVE: Diabetes and hypertension pose significant health risks, especially when poorly managed. ...

Modulation of insulin aggregation by betaine and proline directly observed via real-time super-resolution microscopy.

Protein aggregation is associated with a spectrum of neurodegenerative diseases. Although many small...

Integrative network and computational toxicology reveal the molecular mechanisms in PFOA-induced spermatogenic disorder.

Perfluorooctanoic acid (PFOA), a widely used industrial chemical, poses significant environmental an...

A dynamic model using k-NN algorithm for predicting diabetes and breast cancer.

Healthcare remains a critical focus due to its direct impact on human well-being. Diabetes, currentl...

KDELR3 and YOD1 proteins as critical endoplasmic reticulum stress mediators and potential therapeutic targets in diabetic foot ulcers: An integrated bioinformatics analysis.

BACKGROUND: Diabetic foot ulcers (DFU) represent one of the most severe complications of diabetes me...

Explainable machine learning model incorporating social determinants of health to predict chronic kidney disease in type 2 diabetes patients.

BACKGROUND AND OBJECTIVES: Social determinants of health (SDOH) play a critical role in the onset an...

Prognostic value of the Glucose-to-Albumin ratio in sepsis-related mortality: A retrospective ICU study.

AIMS: To investigate the prognostic value of the glucose-to-albumin ratio (GAR) in predicting 30-day...

Machine learning assisted media optimization for enhanced insulin production in Pseudomonas fluorescens cell factory and scale-up studies.

Diabetes mellitus, a chronic metabolic disorder, is characterized by high blood glucose levels. Exte...

Recent trends in diabetes mellitus diagnosis: an in-depth review of artificial intelligence-based techniques.

Diabetes mellitus (DM) is a highly prevalent chronic condition with significant health and economic ...

IR-MBiTCN: Computational prediction of insulin receptor using deep learning: A multi-information fusion approach with multiscale bidirectional temporal convolutional network.

The insulin receptor (IR) is a transmembrane protein that controls glucose homeostasis and is highly...

Multimodal large language models as assistance for evaluation of thyroid-associated ophthalmopathy.

This study evaluated the potential of multimodal AI chatbots, specifically ChatGPT-4o, in assessing ...

PESI-MS combined with AI to build a prediction model for lymph node metastasis of papillary thyroid cancer.

OBJECTIVE: Construct a prediction model for lymph node metastasis (LNM) in papillary thyroid carcino...

Prediction model of ipsilateral level II lymph node metastasis in papillary thyroid carcinoma.

OBJECTIVES: This study aimed to develop a predictive model for ipsilateral level II lymph node metas...

Advances in artificial intelligence for diabetes prediction: insights from a systematic literature review.

Diabetes mellitus (DM), a prevalent metabolic disorder, has significant global health implications. ...

Development and validation of a predictive machine learning model for postoperative long-term diabetes insipidus following transsphenoidal surgery for sellar lesions.

OBJECTIVE: Diabetes Insipidus (DI) is a common complication that occurs following transsphenoidal su...

Attention in surgical phase recognition for endoscopic pituitary surgery: Insights from real-world data.

BACKGROUND AND OBJECTIVE: Surgical Phase Recognition systems are used to support the automated docum...