A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Precision oncology aims at integrating molecular data into clinical decision making, in order to provide the most suitable therapy and follow-up according to patient’s specific characteristics. A critical step towards this goal is the interpretation of genomic variants, whose presence can be revealed by next generation sequencing. In particular, cancer variant interpretation defines whether the patient harbors genomic alterations that could be targeted by specific drugs, or that were observed as prognostic biomarkers. To standardize somatic interpretation, in 2017 guidelines have been proposed by a working group of associations, including the American Society of Clinical Oncology (ASCO). Automatic tools implementing such guidelines to ease their actual application in the clinical routine are needed. We developed a Rule-based Expert System (ES) that automatically implements ASCO guidelines. ES is an Artificial Intelligence system able to reason over a set of rules and to perform classification, thus emulating human reasoning process. First, we developed automatic pipelines to extract information of over 1500 known diagnostic/prognostic/diagnostic biomarkers from six public databases, including COSMIC and CiVIC. The collected knowledge base is structured in an object-oriented model and the ES is implemented in a Python program through the PyKnow library.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings
EditorsSzymon Wilk, Annette ten Teije, David Riaño
PublisherSpringer Verlag
Pages114-119
Number of pages6
ISBN (Print)9783030216412
DOIs
Publication statusPublished - Jan 1 2019
Event17th Conference on Artificial Intelligence in Medicine, AIME 2019 - Poznan, Poland
Duration: Jun 26 2019Jun 29 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11526 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th Conference on Artificial Intelligence in Medicine, AIME 2019
CountryPoland
CityPoznan
Period6/26/196/29/19

Fingerprint

Rule-based Systems
Expert System
Expert systems
Oncology
Biomarkers
Genomics
Diagnostics
Python
Ports and harbors
Knowledge Base
Object-oriented
Sequencing
Therapy
Artificial intelligence
Artificial Intelligence
Cancer
Drugs
Reasoning
Pipelines
Decision making

Keywords

  • Expert System
  • Somatic variant interpretation
  • Standard guidelines

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Nicora, G., Limongelli, I., Cova, R., Della Porta, M. G., Malcovati, L., Cazzola, M., & Bellazzi, R. (2019). A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines. In S. Wilk, A. ten Teije, & D. Riaño (Eds.), Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings (pp. 114-119). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11526 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-21642-9_15

A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines. / Nicora, Giovanna; Limongelli, Ivan; Cova, Riccardo; Della Porta, Matteo Giovanni; Malcovati, Luca; Cazzola, Mario; Bellazzi, Riccardo.

Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings. ed. / Szymon Wilk; Annette ten Teije; David Riaño. Springer Verlag, 2019. p. 114-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11526 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Nicora, G, Limongelli, I, Cova, R, Della Porta, MG, Malcovati, L, Cazzola, M & Bellazzi, R 2019, A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines. in S Wilk, A ten Teije & D Riaño (eds), Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11526 LNAI, Springer Verlag, pp. 114-119, 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Poznan, Poland, 6/26/19. https://doi.org/10.1007/978-3-030-21642-9_15
Nicora G, Limongelli I, Cova R, Della Porta MG, Malcovati L, Cazzola M et al. A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines. In Wilk S, ten Teije A, Riaño D, editors, Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings. Springer Verlag. 2019. p. 114-119. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-21642-9_15
Nicora, Giovanna ; Limongelli, Ivan ; Cova, Riccardo ; Della Porta, Matteo Giovanni ; Malcovati, Luca ; Cazzola, Mario ; Bellazzi, Riccardo. / A rule-based expert system for automatic implementation of somatic variant clinical interpretation guidelines. Artificial Intelligence in Medicine - 17th Conference on Artificial Intelligence in Medicine, AIME 2019, Proceedings. editor / Szymon Wilk ; Annette ten Teije ; David Riaño. Springer Verlag, 2019. pp. 114-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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