Endocrinology

Applications of machine and deep learning to thyroid cytology and histopathology: a review.

This review synthesises past research into how machine and deep learning can improve the cyto- and histopathology processing pipelines for thyroid cancer diagnosis. The current gold-standard preoperative technique of fine-needle aspiration cytology has high interobserver variability, often returns indeterminate samples and cannot reliably identify some pathologies; histopathology analysis addresse...

Deep-learning-based natural-language-processing models to identify cardiovascular disease hospitalisations of patients with diabetes from routine visits' text.

Writing notes is the most widespread method to report clinical events. Therefore, most of the information about the disease history of a patient remains locked behind free-form text. Natural language processing (NLP) provides a solution to automatically transform free-form text into structured data. In the present work, electronic healthcare records data of patients with diabetes were used to deve...

Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program.

PURPOSE: We examine the rate of and reasons for follow-up in an Artificial Intelligence (AI)-based workflow for diabetic retinopathy (DR) screening re...

Performance of CT-based deep learning in diagnostic assessment of suspicious lateral lymph nodes in papillary thyroid cancer: a prospective diagnostic study.

BACKGROUND: Preoperative evaluation of the metastasis status of lateral lymph nodes (LNs) in papillary thyroid cancer is challenging. Strategies for u...

Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study.

Accurate tumor identification during surgical excision is necessary for neurosurgeons to determine the extent of resection without damaging the surrou...

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from .

Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant ga...

Effectiveness of Nicotinamide Phosphoribosyltransferase/Pre-B Cell Colony-enhancing Factor/Visfatin in preventing High Glucose-induced Neurotoxicity in an In-vitro Model of Diabetic Neuropathy.

INTRODUCTION: Diabetic neuropathy is a well-known complication of diabetes. Recently, hyperglycemia-induced toxicity has been confirmed to participate...

Risk prediction models for postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a scoping review.

OBJECTIVE: The objective of this scoping review was to investigate the effectiveness and limitations of risk prediction models for postpartum glucose ...

Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation.

BACKGROUND: Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult popula...

Trimester-specific exposure to triclocarban during pregnancy: Associations with oxidative stress and size at birth.

Triclocarban (TCC) is an extensively used antimicrobial agent that exhibits endocrine disrupt potential, but its effects on fetal growth remain largel...

The performance of deep learning on thyroid nodule imaging predicts thyroid cancer: A systematic review and meta-analysis of epidemiological studies with independent external test sets.

BACKGROUND AND AIMS: It is still controversial whether deep learning (DL) systems add accuracy to thyroid nodule imaging classification based on the r...

Cholesterol Levels, Hormone Replacement Therapy, and Incident Dementia among Older Adult Women.

Previous studies revealed that hormone replacement therapy (HRT) probably has a protective effect for preventing dementia in post-menopausal women. Ho...

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach.

Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known as diabetes mellitus, which is a chronic conditio...

Insulin signaling in insulin-dysregulated Icelandic horses.

The underlying molecular mechanisms leading to insulin dysregulation are poorly understood in horses. Therefore, this study aimed to determine if insu...

Healthcare Big Data in Hong Kong: Development and Implementation of Artificial Intelligence-Enhanced Predictive Models for Risk Stratification.

Routinely collected electronic health records (EHRs) data contain a vast amount of valuable information for conducting epidemiological studies. With t...

Electroencephalographic abnormalities in children with type 1 diabetes mellitus: a prospective study.

BACKGROUND/AIM: The aim herein was to investigate epileptiform discharges on electroencephalogram (EEG), their correlation with glutamic acid decarbox...

Deep learning to assist composition classification and thyroid solid nodule diagnosis: a multicenter diagnostic study.

OBJECTIVES: This study aimed to propose a deep learning (DL)-based framework for identifying the composition of thyroid nodules and assessing their ma...

Pediatric Psoriasis Associated with Van Wyk Grumbach Syndrome: A case report.

INTRODUCTION: Psoriasis is a common chronic inflammatory condition, often beginning in childhood in approximately one-third of cases. It can be associ...

Normal intellectual ability and hyperprolactinemia as unique clinical manifestations of congenital hypothyroidism: A case report and review of hypotheses.

Congenital hypothyroidism is the deficiency of thyroid hormone in infants and hyperprolactinemia is frequently observed. Previously reported cases typ...

An eXplainable Artificial Intelligence analysis of Raman spectra for thyroid cancer diagnosis.

Raman spectroscopy shows great potential as a diagnostic tool for thyroid cancer due to its ability to detect biochemical changes during cancer develo...