An ontology-driven clinical decision support system (IDDAP) for infectious disease diagnosis and antibiotic prescription

Artificial Intelligence in Medicine

Volumn 86, Issue , 2018, Pages 20-32

  Shen, Ying ^a   Yuan, Kaiqi ^a   Chen, Daoyuan ^a   Colloc, Joël ^b   Yang, Min ^c   Li, Yaliang ^d   Lei, Kai ^a  

^a PEKING UNIVERSITY   (China)

^b UNIVERSITÉ DU HAVRE   (France)

^c INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

^d TENCENT AI LAB   (China)

Author keywords

Antibiotics prescription; Clinical decision support; Decision support system; Diagnosis classification; Ontology

Indexed keywords

ANTIBIOTICS; ARTIFICIAL INTELLIGENCE; BACTERIA; BEHAVIORAL RESEARCH; COMPUTER AIDED DIAGNOSIS; DECISION MAKING; DECISION SUPPORT SYSTEMS; DIGESTIVE SYSTEM; DISEASE CONTROL; DRUG INTERACTIONS; DRUG THERAPY; KNOWLEDGE BASED SYSTEMS; LEARNING ALGORITHMS; LEARNING SYSTEMS; ONTOLOGY; PLASMA DIAGNOSTICS; REACTION RATES; SEARCH ENGINES;

CLINICAL DECISION SUPPORT; CLINICAL DECISION SUPPORT SYSTEMS; COMPUTATIONAL TECHNIQUE; DATA DRIVEN DECISION; DECISION-MAKING SYSTEMS; INTERACTION RELATIONSHIP; RECEIVER OPERATING CHARACTERISTIC (ROC) CURVES; SENSITIVITY AND SPECIFICITY;

DISEASES;

ANTIBIOTIC AGENT; ANTIINFECTIVE AGENT; SULTAMICILLIN;

ANTIBIOTIC THERAPY; ARTICLE; ARTIFICIAL INTELLIGENCE; BACTERIAL INFECTION; CLINICAL DECISION SUPPORT SYSTEM; INFECTION; MYCOSIS; ONTOLOGY; PRESCRIPTION; PRIORITY JOURNAL; SELF REPORT; SOFTWARE; VIRUS INFECTION; BIOLOGICAL ONTOLOGY; CLINICAL DECISION MAKING; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED DRUG THERAPY; COMPUTER INTERFACE; DECISION SUPPORT SYSTEM; HUMAN; MACHINE LEARNING; MICROBIOLOGY; PREDICTIVE VALUE; RECEIVER OPERATING CHARACTERISTIC; REPRODUCIBILITY;

ANTI-BACTERIAL AGENTS; BACTERIAL INFECTIONS; BIOLOGICAL ONTOLOGIES; CLINICAL DECISION-MAKING; DECISION SUPPORT SYSTEMS, CLINICAL; DECISION SUPPORT TECHNIQUES; DIAGNOSIS, COMPUTER-ASSISTED; DRUG PRESCRIPTIONS; DRUG THERAPY, COMPUTER-ASSISTED; HUMANS; MACHINE LEARNING; PREDICTIVE VALUE OF TESTS; REPRODUCIBILITY OF RESULTS; ROC CURVE; USER-COMPUTER INTERFACE;

EID: 85041532672     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2018.01.003     Document Type: Article

References (38)

1. Magiorakos, A.P., Srinivasan, A., Carey, R.B., Carmeli, Y., Falagas, M.E., Giske, C.G., et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect 18 (2012), 268–281.
2. Amarenco, P., Benavente, O., Goldstein, L.B., Callahan, A., Sillesen, H., Hennerici, M.G., et al. Stroke prevention by aggressive reduction in cholesterol levels investigators, results of the stroke prevention by aggressive reduction in cholesterol levels (SPARCL) trial by stroke subtypes. Stroke 40 (2009), 1405–1409.
3. Shen, Y., Colloc, J., Jacquet-Andrieu, A., Lei, K., Emerging medical informatics with case-based reasoning for aiding clinical decision in multi-agent system. J Biomed Inform 56 (2015), 307–317.
4. Bonczek, R., Holsapple, C., Whinston, A., Foundations of Decision Support Systems. 2014, Academic Press Boston.
5. Kuperman, G.J., Gardner, R.M., Pryor, T.A., HELP: A Dynamic Hospital Information System. 2013, Springer Science & Business Media, New York.
6. Evans, R.S., Larsen, R.A., Burke, J.P., Gardner, R.M., Meier, F.A., Jacobson, J.A., et al. Computer surveillance of hospital-acquired infections and antibiotic use. J. Am. Med. Assoc. 256 (1986), 1007–1011.
7. Burke, J.P., Classen, D.C., Pestotnik, S.L., Evans, R.S., Stevens, L.E., The HELP system and its application to infection control. J Hosp Infect 18 (1991), 424–431.
8. Johnson, J.H., The timing of prophylactic administration of antibiotics and the risk of surgical-wound infection. AORN J 56 (1992), 347–348.
9. Singh, N., Rogers, P., Atwood, C.W., Wagener, M.M., Yu, V.L., Short-course empiric antibiotic therapy for patients with pulmonary infiltrates in the intensive care unit. A proposed solution for indiscriminate antibiotic prescription. Am J Respir Crit Care Med 162 (2000), 505–511.
10. Morrell, R., Wasilauskas, B., Winslow, R., Personal computer-based expert system for quality assurance of antimicrobial therapy. Am J Hosp Pharm 50 (1993), 2067–2073.
11. Leibovici, L., Fishman, M., Schonheyder, H.C., Riekehr, C., Kristensen, B., Shraga, I., et al. A causal probabilistic network for optimal treatment of bacterial infections. IEEE Trans Knowl Data Eng 12 (2000), 517–528.
12. Maedche, A., Ontology Learning for the Semantic Web. 2012, Springer Science & Business Media, New York.
13. Robinson, P., Bauer, S., Introduction to Bio-Ontologies. 2011, CRC Press, Boca Raton.
14. Köhler, S., Schulz, M.H., Krawitz, P., Bauer, S., Dölken, S., Ott, C.E., et al. Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet 85 (2009), 457–464.
15. Bauer, S., Köhler, S., Schulz, M.H., Robinson, P.N., Bayesian ontology querying for accurate and noise-tolerant semantic searches. Bioinformatics 28 (2012), 2502–2508.
16. Bonczek, R., Holsapple, C., Whinston, A., Foundations of Decision Support Systems. 2014, Academic Press, Zurich Switzerland.
17. Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W., Ceusters, W., et al. The OBO foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol 25 (2007), 1251–1255.
18. Cowell, L., Smith, B., Infectious disease ontology. Sintchenko, V., (eds.) Infectious Disease Informatics, 2010, Springer, New York, 373–395.
19. Federhen, S., The NCBI taxonomy database. Nucleic Acids Res 40 (2012), D136–D143.
20. Köhler, S., Doelken, S.C., Mungall, C.J., et al. The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res 42 (2014), D966–D974.
21. Wishart, D.S., Knox, C., Guo, A.C., Shrivastava, S., Hassanali, M., Stothard, P., et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res 34 (2006), D668–D672.
22. Schriml, L.M., Arze, C., Nadendla, S., Chang, Y.W., Mazaitis, M., Felix, V., et al. Disease ontology: a backbone for disease semantic integration. Nucleic Acids Res 40 (2012), D940–D946.
23. Hopkins Medicine Antibiotic guidelines, 2015-2016, Johns Hopkins Medicine, Baltimore, http://www.hopkinsmedicine.org/amp/guidelines/antibiotic_guidelines.pdf, 2016 (accessed 23 October 2016).
24. Bodenreider, O., The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Res 32 (2004), D267–D270.
25. Medicine Wikipedia, https://en.wikipedia.org/wiki/Medicine, 2017 (accessed 10 January 2017).
26. Centers for Disease Control and Prevention, International classification of diseases, 9th revision, clinical modification (ICD-9-CM). https://www.cdc.gov/nchs/icd/icd9.htm, 2015 (accessed 13 October 2017).
27. Wikipedia, List of antibiotics. https://en.wikipedia.org/wiki/List_of_antibiotics, 2017 (accessed 13 October 2017).
28. Jernite, Y., Halpern, Y., Horng, S., Sontag, S., Predicting chief complaints at triage time in the emergency department. NIPS Workshop on Machine Learning for Clinical Data Analysis and Healthcare, 2013.
29. Knublauch, H., Fergerson, R.W., Noy, N.F., Musen, M.A., The Protégé OWL plugin: an open development environment for semantic web applications. International Semantic Web Conference 3298 (2004), 229–243.
30. Angles, R., Gutierrez, C., Survey of graph database models. ACM Comput Surv, 40, 2008, 1.
31. Holzschuher, F., Peinl, R., Performance of graph query languages: comparison of cypher, gremlin and native access in Neo4j. Proceedings of the Joint EDBT/ICDT 2013 Workshops, ACM, 2013, 195–204.
32. Robinson, I., Webber, J., Eifrem, E., Graph Databases. 2013, O'Reilly Media, Inc., Sebastopol.
33. Ryan, K., Ray, C., Sherris, J., Sherris Medical Microbiology. 2004, McGraw-Hill, New York.
34. Singh, S.B., Jayasuriya, H., Ondeyka, J.G., Herath, K.B., Zhang, C., Zink, D.L., et al. Isolation structure, and absolute stereochemistry of Platensimycin, A broad spectrum antibiotic discovered using an antisense differential sensitivity strategy. J Am Chem Soc 128 (2006), 11916–11920.
35. Reese, R., Betts, R., Gumustop, B., Handbook of Antibiotics. 2000, Lippincott Williams & Wilkins, Philadelphia.
36. Fawcett, T., ROC graphs: notes and practical considerations for researchers. Mach. Learn. 31 (2004), 1–38.
37. Lei, K., Zhang, L., Shen, Y., Wu, J., Syndromes diagnostic model for coronary artery disease (CAD): an improved naïve Bayesian classification model based on attribute relevancy. 2017 IEEE 2nd International Conference on Big Data analysis (ICBDA 2017), Beijing, China, 2017, 897–902.
38. Mitraka, E., Topalis, P., Dialynas, E., Dritsou, V., Louis, C., IDODEN: An Ontology for Dengue. 2012, ICBO.