Endocrinology

Latest AI and machine learning research in endocrinology for healthcare professionals.

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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...

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 ...

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. ...

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...

Deep reinforcement learning for Type 1 Diabetes: Dual PPO controller for personalized insulin management.

BACKGROUND: Managing blood glucose levels in Type 1 Diabetes Mellitus (T1DM) is essential to prevent...

ChatGPT-4's Accuracy in Estimating Thyroid Nodule Features and Cancer Risk From Ultrasound Images.

OBJECTIVE: To evaluate the performance of GPT-4 and GPT-4o in accurately identifying features and ca...

Deep learning based on ultrasound images predicting cervical lymph node metastasis in postoperative patients with differentiated thyroid carcinoma.

OBJECTIVES: To develop a deep learning (DL) model based on ultrasound (US) images of lymph nodes for...

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