Endocrinology

EFFICACY AND PROGNOSIS IN PATIENTS WITH PAPILLARY THYROID CANCER WITH POSTOPERATIVE PREABLATIVE STIMULATED THYROGLOBULIN ABOVE 10 NG/ML AFTER INITIAL THERAPY WITH RADIOIODINE.

OBJECTIVE: Few prognostic analyses have been conducted for papillary thyroid cancer (PTC) patients with preablative stimulated Tg >10 ng/mL. We investigated the therapeutic responses and prognosis of these patients after the initial radioiodine (RAI) therapy.

PREDICTORS OF TSH NORMALIZATION IN THYROTOXICOSIS PATIENTS AFTER TREATMENT.

CONTEXT: Understanding factors delaying recovery in thyrotoxicosis patients is crucial for optimizing treatment plan.

Development of a Deep Learning Tool to Support the Assessment of Thyroid Follicular Cell Hypertrophy in the Rat.

Thyroid tissue is sensitive to the effects of endocrine disrupting substances, and this represents a significant health concern. Histopathological ana...

Exploring the subtle and novel renal pathological changes in diabetic nephropathy using clustering analysis with deep learning.

To decrease the number of chronic kidney disease (CKD), early diagnosis of diabetic kidney disease is required. We performed invariant information clu...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

This study sought to establish and validate an interpretable CT radiomics-based machine learning model capable of predicting post-acute pancreatitis d...

Hybrid Control Policy for Artificial Pancreas via Ensemble Deep Reinforcement Learning.

OBJECTIVE: The artificial pancreas (AP) shows promise for closed-loop glucose control in type 1 diabetes mellitus (T1DM). However, designing effective...

Effects of exogenous insulin supplementation on lipid metabolism in peripartum obese dairy cows.

Cows with high body condition scores experience more severe negative energy balance (NEB) and undergo mobilization of more body fat during the peripar...

Immunometabolic alterations in type 2 diabetes mellitus revealed by single-cell RNA sequencing: insights into subtypes and therapeutic targets.

BACKGROUND: Type 2 Diabetes Mellitus (T2DM) represents a major global health challenge, marked by chronic hyperglycemia, insulin resistance, and immun...

NDUFA11 may be the disulfidptosis-related biomarker of ischemic stroke based on integrated bioinformatics, clinical samples, and experimental analyses.

BACKGROUND: Programmed cell death plays an important role in neuronal injury and death after ischemic stroke (IS), leading to cellular glucose deficie...

Deep Learning Technology for Classification of Thyroid Nodules Using Multi-View Ultrasound Images: Potential Benefits and Challenges in Clinical Application.

BACKGRUOUND: This study aimed to evaluate the applicability of deep learning technology to thyroid ultrasound images for classification of thyroid nod...

Weakly-supervised thyroid ultrasound segmentation: Leveraging multi-scale consistency, contextual features, and bounding box supervision for accurate target delineation.

Weakly-supervised learning (WSL) methods have gained significant attention in medical image segmentation, but they often face challenges in accurately...

Screening of obstructive sleep apnea and diabetes mellitus -related biomarkers based on integrated bioinformatics analysis and machine learning.

BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two...

Predictive value of machine learning for the progression of gestational diabetes mellitus to type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to explore the early predictive value of machine learning (ML) models for the progression of gestational diabe...

Research on detection methods of related substances and degradation products of the antitumor drug selpercatinib.

BACKGROUND: Selpercatinib, a selective RET kinase inhibitor, is approved for treating various cancers with RET gene mutations such as RET-rearranged t...

Construction of an anaplastic thyroid cancer stratification signature to guide immune therapy selection and validation of the pivotal gene HLF through experiments.

INTRODUCTION: While most thyroid cancer patients have a favorable prognosis, anaplastic thyroid carcinoma (ATC) remains a particularly aggressive form...

Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer.

Recent evidence indicates that endocrine resistance in estrogen receptor-positive (ER+) breast cancer is closely correlated with phenotypic characteri...

Exploring the triglyceride-glucose index's role in depression and cognitive dysfunction: Evidence from NHANES with machine learning support.

BACKGROUND: Depression and cognitive impairments are prevalent among older adults, with evidence suggesting potential links to obesity and lipid metab...

AntiT2DMP-Pred: Leveraging feature fusion and optimization for superior machine learning prediction of type 2 diabetes mellitus.

Pancreatic α-amylase breaks down starch into isomaltose and maltose, which are further hydrolyzed by α-glucosidase in the intestine into monosaccharid...

DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules.

In this paper, a two-stage task weakly supervised learning algorithm is proposed. It accurately achieved patient-level classification task of benign a...

A hybrid explainable model based on advanced machine learning and deep learning models for classifying brain tumors using MRI images.

Brain tumors present a significant global health challenge, and their early detection and accurate classification are crucial for effective treatment ...