AIMC Topic: Glomerulonephritis, IGA

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Development and Validation of a Predictive Model for Severe Tubular Atrophy/Interstitial Fibrosis in Patients with IgA Nephropathy: Multicenter Retrospective Study.

JMIR medical informatics
BACKGROUND: Severe tubular atrophy/interstitial fibrosis are critical pathological features associated with poor prognosis in IgA nephropathy (IgAN). The early identification of patients at high risk for severe tubular damage could guide clinical man...

Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications.

Scientific reports
Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive manual interpretation as well as unavoidable interpreter-dependent variabilities. We propose artific...

Classification of primary glomerulonephritis using machine learning models: a focus on IgA nephropathy prediction.

BMC nephrology
OBJECTIVE: IgA nephropathy (IgAN) is the most common form of glomerulonephritis worldwide, characterized by immune complex deposition in the glomerular mesangium, leading to mesangial hypercellularity, persistent microhematuria, proteinuria, and prog...

Rapid detection of kidney disease based on urine surface-enhanced Raman spectroscopy and principal components analysis-support vector machine/random forests.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Immunoglobulin A nephropathy (IgAN) and idiopathic membranous nephropathy (IMN) are the most prevalent primary glomerulonephritis (PGN) subtypes and can lead to end-stage renal disease. Conventional diagnostic methods in certain aspects are often lim...

MAL-Net: A Multi-Label Deep Learning Framework Integrating LSTM and Multi-Head Attention for Enhanced Classification of IgA Nephropathy Subtypes Using Clinical Sensor Data.

Sensors (Basel, Switzerland)
BACKGROUND: IgA nephropathy (IgAN) is a leading cause of renal failure, characterized by significant clinical and pathological heterogeneity. Accurate subtype classification remains challenging due to overlapping clinical manifestations and the multi...

Machine learning-based unsupervised phenotypic clustering analysis of patients with IgA nephropathy: Distinct therapeutic responses of different groups.

Chinese medical journal
BACKGROUND: Immunoglobulin A nephropathy (IgAN) has a heterogeneous clinical presentation. Comparison of different IgAN subgroups may facilitate the application of more targeted therapies. This study was aimed to distinct disease phenotypes in IgAN a...

Machine-learning model based on ultrasomics for non-invasive evaluation of fibrosis in IgA nephropathy.

European radiology
OBJECTIVES: To develop and validate an ultrasomics-based machine-learning (ML) model for non-invasive assessment of interstitial fibrosis and tubular atrophy (IF/TA) in patients with IgA nephropathy (IgAN).

Application of cloud server-based machine learning for assisting pathological structure recognition in IgA nephropathy.

Journal of clinical pathology
BACKGROUND: Machine learning (ML) models can help assisting diagnosis by rapidly localising and classifying regions of interest (ROIs) within whole slide images (WSIs). Effective ML models for clinical decision support require a substantial dataset o...

Machine-learning-based identification of patients with IgA nephropathy using a computerized medical billing database.

PloS one
The billing database of the universal healthcare system in Japan potentially includes large-cohort data of patients with immunoglobulin A nephropathy, diagnosis codes aimed at billing should not be directly used for clinical research because of the r...