APPLICATION OF PERSISTENT HOMOLOGY ON BIO-MEDICAL DATA – A CASE STUDY
Petar Sekuloski, Vesna Ristovska
Abstract
Petar Sekuloski, Vesna Ristovska
Abstract
In this paper we introduce, analyze and apply persistent homology, one of the main algorithms of TDA, on some real data sets from the bio-medical field. Topological data analysis (TDA) is a field which is a synergy between mathematics, data science and computer science. The main goal of TDA is studying the shape of data using topological techniques. TDA proposes new algorithms that deal with these problems based on tools or concepts from algebraic topology and pure mathematics. We analyze the results and give a topological characterization of the dataset and propose to use them in future work.
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In this paper we introduce, analyze and apply persistent homology, one of the main algorithms of TDA, on some real data sets from the bio-medical field. Topological data analysis (TDA) is a field which is a synergy between mathematics, data science and computer science. The main goal of TDA is studying the shape of data using topological techniques. TDA proposes new algorithms that deal with these problems based on tools or concepts from algebraic topology and pure mathematics. We analyze the results and give a topological characterization of the dataset and propose to use them in future work.
Key concepts: Topological data analysis, Persistent homology, Algebraic topology, Homology (biology), Algebraic number, Field (mathematics), Computer science, Theoretical computer science