Persistent homology approach distinguishes potential pattern between “Early” and “Not Early” hepatic decompensation groups using MRI modalities Article Swipe

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Decompensation Topological data analysis Medicine Persistent homology Treatment modality Algebraic number Computer science Mathematics Internal medicine Algorithm Mathematical analysis

Yashbir Singh , William Jons , Gian Marco Conte , Jaidip Jagtap , Kuan Zhang , Joseph D. Sobek , Pouria Rouzrokh , John E. Eaton , Bradley J. Erickson ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.1515/cdbme-2021-2124 · OA: W4200013595

Primary sclerosis cholangitis (PSC) predisposes individuals to liver failure, but it is challenging for radiologists examining radiologic images to predict which patients with PSC will ultimately develop liver failure. Motivated by algebraic topology, a topological data analysis - inspired framework was adopted in the study of the imaging pattern between the “Early Decompensation” and “Not Early” groups. The results demonstrate that the proposed methodology discriminates “Early Decompensation” and “Not Early” groups. Our study is the first attempt to provide a topological representation-based method into early hepatic decompensation and not early groups.