Endocrinology

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

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Comparison of Different Doses of Clonidine as an Additive to Intrathecal Isobaric Levobupivacaine in Patients Undergoing Infraumbilical Surgeries.

BACKGROUND: Spinal anesthesia is a safe, reliable, and inexpensive technique with the advantage of p...

Hybrid artificial fish particle swarm optimizer and kernel extreme learning machine for type-II diabetes predictive model.

The World Health Organization (WHO) estimated that in 2016, 1.6 million deaths caused were due to di...

Assessment of medication self-administration using artificial intelligence.

Errors in medication self-administration (MSA) lead to poor treatment adherence, increased hospitali...

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors.

Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory ...

Handcrafted MRI radiomics and machine learning: Classification of indeterminate solid adrenal lesions.

PURPOSE: To assess a radiomic machine learning (ML) model in classifying solid adrenal lesions (ALs)...

Deep learning-based detection and stage grading for optimising diagnosis of diabetic retinopathy.

AIMS: To establish an automated method for identifying referable diabetic retinopathy (DR), defined ...

Machine learning for the prediction of bone metastasis in patients with newly diagnosed thyroid cancer.

OBJECTIVES: This study aimed to establish a machine learning prediction model that can be used to pr...

A deep learning method for HLA imputation and trans-ethnic MHC fine-mapping of type 1 diabetes.

Conventional human leukocyte antigen (HLA) imputation methods drop their performance for infrequent ...

A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhib...

Screening of a novel free fatty acid receptor 1 (FFAR1) agonist peptide by phage display and machine learning based-amino acid substitution.

Free fatty acid receptor 1 (FFAR1 or GPR40) has attracted attention for the treatment of type 2 diab...

The effect of diabetes on major robotic hepatectomy.

Studies regarding the influence of diabetes on perioperative outcomes after major hepatectomy are co...

Deep Learning-Based Diabetic Retinopathy Severity Grading System Employing Quadrant Ensemble Model.

The diabetic retinopathy accounts in the deterioration of retinal blood vessels leading to a serious...

GestAltNet: aggregation and attention to improve deep learning of gestational age from placental whole-slide images.

The placenta is the first organ to form and performs the functions of the lung, gut, kidney, and end...

Adequacy and Effectiveness of Watson For Oncology in the Treatment of Thyroid Carcinoma.

BACKGROUND: IBM's Watson for Oncology (WFO) is an artificial intelligence tool that trains by acquir...

Machine learning-based prediction model using clinico-pathologic factors for papillary thyroid carcinoma recurrence.

This study analyzed the prognostic significance of clinico-pathologic factors, including the number ...

Machine Learning in Preoperative Prediction of Postoperative Immediate Remission of Histology-Positive Cushing's Disease.

BACKGROUND: There are no established accurate models that use machine learning (ML) methods to preop...

Deep learning differentiates between healthy and diabetic mouse ears from optical coherence tomography angiography images.

We trained a deep learning algorithm to use skin optical coherence tomography (OCT) angiograms to di...

Protein glycation - biomarkers of metabolic dysfunction and early-stage decline in health in the era of precision medicine.

Protein glycation provides a biomarker in widespread clinical use, glycated hemoglobin HbA (A1C). It...

A review on current advances in machine learning based diabetes prediction.

Diabetes is a metabolic disorder comprising of high glucose level in blood over a prolonged period i...

Development and Validation of a Deep Learning Based Diabetes Prediction System Using a Nationwide Population-Based Cohort.

BACKGROUND: Previously developed prediction models for type 2 diabetes mellitus (T2DM) have limited ...

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