Endocrinology

Transforming the management of radiotherapy-induced hypothyroidism in nasopharyngeal carcinoma through an Innovative individualized radiation dosage model: A multicenter retrospective analysis.

PURPOSE: Current guidelines for thyroid radiation dose prescription lack uniformity and fail to consider the unique characteristics of individual patients. This study aimed to develop an individualized thyroid dosing regimen to enhance thyroid protection during radiotherapy.

MIP-based electrochemical sensor with machine learning for accurate ZIKV detection in protein- and glucose-rich urine.

Nowadays, a multitude of biosensors are being developed worldwide. However, a significant challenge arises when these biosensors are tested in real sample environments, as many of them fail to perform as expected. This can lead to ambiguous results and raise concerns about their reliability. In many cases, further data analysis is required to enhance the clarity and meaningfulness of the outputs. ...

Risk prediction models for patients with recurrent diabetic foot ulcers: A systematic review.

OBJECTIVES: To systematically review published studies on risk prediction models for patients with recurrent diabetic foot ulcers.

CoMMiT: Co-informed inference of microbiome-metabolome interactions via transfer learning

Recent multi-omic microbiome studies enable integrative analysis of microbes and metabolites, uncovering their associations with various host condit...

GroundingDINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models

Accurate and generalizable object segmentation in ultrasound imaging remains a significant challenge due to anatomical variability, diverse imaging ...

Predicting treatment outcome in congenital adrenal hyperplasia using urine steroidomics and machine learning.

OBJECTIVE: Treatment monitoring of individuals with congenital adrenal hyperplasia (CAH) remains unsatisfactory. Comprehensive 24 h urine steroid prof...

HQCM-EBTC: A Hybrid Quantum-Classical Model for Explainable Brain Tumor Classification

We propose HQCM-EBTC, a hybrid quantum-classical model for automated brain tumor classification using MRI images. Trained on a dataset of 7,576 scan...

Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction

Healthcare professionals need effective ways to use, understand, and validate AI-driven clinical decision support systems. Existing systems face two...

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

$\textbf{Objective:}$ Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust BrainA...

BRISC: Annotated Dataset for Brain Tumor Segmentation and Classification with Swin-HAFNet

Accurate segmentation and classification of brain tumors from Magnetic Resonance Imaging (MRI) remain key challenges in medical image analysis, larg...

Machine Learning Prediction of Pancreatitis Risk With Antithyroid Drugs: A Nationwide Retrospective Observational Study.

BACKGROUND: In recent years, there has been increasing data showing that the risk of acute pancreatitis (AP) is increased in patients using methimazol...

Diabetes Prediction and Management Using Machine Learning Approaches

Diabetes has emerged as a significant global health issue, especially with the increasing number of cases in many countries. This trend Underlines t...

Structural Insights into the Substrate Egress Pathways Explains Specificity and Inhibition of Human Glucose Transporters (GLUT1 and GLUT9).

Glucose transporters (GLUTs) play critical roles in cellular energy homeostasis and substrate-specific transport. Dysfunctional mutations can cause GL...

Development of a machine learning model for predicting cardiovascular risk factors and major adverse cardiovascular events in young adults with glucose metabolism disorders.

BACKGROUND: Glucose metabolism disorders (GMDs) are a serious global public health issue, characterized by a high incidence rate and youthfulness. GMD...

Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study.

BACKGROUND: Insulin resistance (IR), a precursor to type 2 diabetes and a major risk factor for various chronic diseases, is becoming increasingly pre...

Adapting Vision-Language Foundation Model for Next Generation Medical Ultrasound Image Analysis

Medical ultrasonography is an essential imaging technique for examining superficial organs and tissues, including lymph nodes, breast, and thyroid. ...

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 ligands have been found to modulate or inhibit pr...

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. Retinal evaluation though fundus photography can p...

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 and biological toxicity, particularly affecting repr...

KDELR3 and YOD1 proteins as critical endoplasmic reticulum stress mediators and potential therapeutic targets in diabetic foot ulcers: An integrated bioinformatics analysis.

BACKGROUND: Diabetic foot ulcers (DFU) represent one of the most severe complications of diabetes mellitus and are closely associated with persistent ...