17 results for “topic:rheumatoid-arthritis”
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Cast different EHR (electronic health record) layers to a shared latent space to identify patient subtypes
This project develops a machine learning model to classify individuals as healthy, having rheumatoid arthritis (RA), or systemic lupus erythematosus (SLE) using RNA-Seq gene expression data. The project also identifies significant genes as potential biomarkers, leveraging SGDClassifier and XGBoost models.
Bioinformatics analysis of rheumatoid arthritis using GEO datasets to identify DEGs, hub genes, and enriched pathways through PPI network and enrichment analysis.
Machine learning pipeline to enhance patient triaging by predicting diagnosis based on referral letters
Repository for Multi Omics data Integration for Transcriptomics and Metabolomics in RA mouse models
Two staged approach to predict joint level damage from hand and feet radiographs
This was my bachelor's thesis project. We attempted to design a system that can quantify joint stiffness and handgrip, to create a standard for measuring rheumatoid arthritis disease progression.
Right Prediction, Wrong Reasoning: Uncovering LLM Misalignment in RA Disease Diagnosis
End-to-end GWAS pipeline for rheumatoid arthritis (NARAC): QC, PCA-based stratification control, sex-stratified mixed-model association testing, PRS, and LD score regression.
R code for the data managment and statistical analysis performed for the paper Associations Between Rheumatoid Arthritis, Incident Heart Failure and Left Ventricular Ejection Fraction
Explainable machine learning classification for rheumatoid arthritis using B cell receptor sequences
Repository for supplementary data
This is the Github repository for the 24 week results of the NORD-STAR trial
Github repository for the Nord-Star 48 week analysis
Code for Jonsson*, Zhang*, et al, TteK (Granzyme K+ CD8 T cells), Science Translational Medicine, 2022: the core population of inflamed human tissue-associated CD8 T cells.
Shiny interface for CD4 T-cell ATAC-seq from Rheumatoid Arthritis patients.