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Machine learning-based cardiac activity non-linear analysis for discriminating COVID-19 patients with different degrees of severity.

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A Parallel Algorithm for Counting Subgraphs in Complex Networks., , and . BIOSTEC (Selected Papers), volume 127 of Communications in Computer and Information Science, page 380-393. Springer, (2010)Novel features for time series analysis: a complex networks approach., , , and . Data Min. Knowl. Discov., 36 (3): 1062-1101 (2022)Correction to: Sound reasoning in tock-CSP., , and . Acta Informatica, 59 (2-3): 283 (2022)Sound reasoning in tock-CSP., , and . Acta Informatica, 59 (1): 125-162 (2022)Angelic Processes.. CoRR, (2015)A Survey on Subgraph Counting: Concepts, Algorithms and Applications to Network Motifs and Graphlets., , , , and . CoRR, (2019)Novel Features for Time Series Analysis: A Complex Networks Approach., , , and . CoRR, (2021)RUP Alignment and Coverage Analysis of CMMI ML2 Process Areas for the Context of Software Projects Execution., , , , and . SWQD, volume 166 of Lecture Notes in Business Information Processing, page 214-228. Springer, (2014)Implementation of GDPR: Learning with a Local Administration Case Study., , and . SmartCity360°, volume 323 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, page 205-216. Springer, (2019)Machine learning-based cardiac activity non-linear analysis for discriminating COVID-19 patients with different degrees of severity., , , , , , , , , and . Biomed. Signal Process. Control., 87 (Part A): 105558 (January 2024)