Endocrinology

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

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Intelligent type 2 diabetes risk prediction from administrative claim data.

Type 2 diabetes is a chronic, costly disease and is a serious global population health problem. Yet,...

Graves Disease Following Subacute Thyroiditis in a Chinese Man.

BACKGROUND/OBJECTIVE: The development of Graves disease (GD) after subacute thyroiditis (SAT) is rar...

Diagnosis of Pituitary Adenoma Biopsies by Ultrahigh Resolution Optical Coherence Tomography Using Neuronal Networks.

OBJECTIVE: Despite advancements of intraoperative visualization, the difficulty to visually distingu...

Characterizing shared and distinct symptom clusters in common chronic conditions through natural language processing of nursing notes.

Data-driven characterization of symptom clusters in chronic conditions is essential for shared clust...

An ontology network for Diabetes Mellitus in Mexico.

BACKGROUND: Medical experts in the domain of Diabetes Mellitus (DM) acquire specific knowledge from ...

Federated Learning for Microvasculature Segmentation and Diabetic Retinopathy Classification of OCT Data.

PURPOSE: To evaluate the performance of a federated learning framework for deep neural network-based...

Machine-Learning Prediction of Postoperative Pituitary Hormonal Outcomes in Nonfunctioning Pituitary Adenomas: A Multicenter Study.

OBJECTIVE: No accurate predictive models were identified for hormonal prognosis in non-functioning p...

Mulberry leaves ameliorate diabetes via regulating metabolic profiling and AGEs/RAGE and p38 MAPK/NF-κB pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Mulberry leaves have been used as traditional hypoglycemic medicine-...

Automated detection of severe diabetic retinopathy using deep learning method.

PURPOSE: The purpose of this study is to develop and validate the intelligent diagnosis of severe DR...

Image-guided MALDI mass spectrometry for high-throughput single-organelle characterization.

Peptidergic dense-core vesicles are involved in packaging and releasing neuropeptides and peptide ho...

Machine Learning Based Diabetes Classification and Prediction for Healthcare Applications.

The remarkable advancements in biotechnology and public healthcare infrastructures have led to a mom...

Perioperative Outcomes of a Hydrocortisone Protocol after Endonasal Surgery for Pituitary Adenoma Resection.

 In pituitary adenomas (PAs), the use of postoperative steroid supplementation remains controversia...

Claims-based algorithms for common chronic conditions were efficiently constructed using machine learning methods.

Identification of medical conditions using claims data is generally conducted with algorithms based ...

Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei: A quantitative analysis.

When approaching thyroid gland tumor classification, the differentiation between samples with and wi...

Hyperglycemia Identification Using ECG in Deep Learning Era.

A growing number of smart wearable biosensors are operating in the medical IoT environment and those...

Magneto-Responsive Microneedle Robots for Intestinal Macromolecule Delivery.

Oral administration is the most convenient and commonly used approach for drug delivery, while it is...

GenNet framework: interpretable deep learning for predicting phenotypes from genetic data.

Applying deep learning in population genomics is challenging because of computational issues and lac...

The Importance of Close Follow-Up in Patients with Early-Grade Diabetic Retinopathy: A Taiwan Population-Based Study Grading via Deep Learning Model.

(1) Background: Diabetic retinopathy (DR) can cause blindness. Current guidelines on diabetic eye ca...

Transoral robotic resection of a lingual thyroid: a novel treatment for obstructive sleep apnoea.

A 34-year-old woman with a history of congenital hypothyroidism and 15 years of obstructive sleep ap...

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