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Using machine learning to predict osteoarthritis

As part of the Rheumatology research team, I had the opportunity to work on the implementation and interpretation of genome-wide association studies (GWAS) to search for SNPs associated with different structural and pain phenotypes related to osteoarthritis, working with the available cohorts and calculating Polygenic Risk Scores (PRS) from them.



I also developed artificial intelligence algorithms for predicting phenotypes.

of rapid progression of pain and structure in osteoarthritis, and wrote the corresponding report. In turn, I integrated the radiological, genomic, epigenetic,

proteomics and questionnaires collected to classify patients and create the databases used by the algorithms.


The corresponding papers are in process.

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