SEPHYRES: A Medical Diagnosis Model based on Semantic Pseudo-Fuzzy Plan and Radar-form Interface

Authors

  • Ali SANAEIFAR Payam-e-Noor University of Tehran (PNU), Tehran, Iran. http://orcid.org/0000-0001-5164-4533
  • Mahmood TARA Department of Medical Informatics, School of Medicine, Mashhad University of Medical Science, Mashhad, Iran
  • Mitra AHADI Assistant professor of gastrointestinal and liver disease, Ghaem hospital, Department of Internal Medicine, Mashhad University of Medical Science (MUMS), Mashhad, Iran
  • Ali BAHARI Endoscopic & Minimally Invasive Surgery Research Center, Mashhad University of Medical Science (MUMS), Mashhad, Iran
  • Ahmad FARAAHI Department of Computer Engineering and Information Technology, Payam-e-Noor University of Tehran (PNU), Tehran, PO.BOX 19395-3697, Iran

Keywords:

Clinical information systems, Clinical decision support, Computer assisted decision making, Knowledge modeling and representation, Telemedicine and telehealth, Computer assisted diagnosis

Abstract

Clinical decision support systems have emerged to help users and patients. Despite the exciting developments, physicians still have not fully accepted and included the decision support systems in daily practice. Some of resistance is related to expressivity and user interface. After publishing SEPHYRES 1, a medical diagnostic assistant focused on only detailed pain descriptors, a more explicit advanced plan has been recommended to relieve above mentioned barriers. Having combined the pseudo-fuzzy and semantic layers could improve expressivity challenge in using diagnostic terms. In addition, applying visual-pain-area module in detailed granularity along with natural language processing module and radar-form interface, a new point of view for the user-interface-related problems has been addressed for future researchers.

Author Biographies

Ali SANAEIFAR, Payam-e-Noor University of Tehran (PNU), Tehran, Iran.

Payame Noor University of Tehran

Mahmood TARA, Department of Medical Informatics, School of Medicine, Mashhad University of Medical Science, Mashhad, Iran

Department of Medical Informatics

Mitra AHADI, Assistant professor of gastrointestinal and liver disease, Ghaem hospital, Department of Internal Medicine, Mashhad University of Medical Science (MUMS), Mashhad, Iran

Department of Internal Medicine

Ali BAHARI, Endoscopic & Minimally Invasive Surgery Research Center, Mashhad University of Medical Science (MUMS), Mashhad, Iran

Endoscopic & Minimally Invasive Surgery Research Center

Ahmad FARAAHI, Department of Computer Engineering and Information Technology, Payam-e-Noor University of Tehran (PNU), Tehran, PO.BOX 19395-3697, Iran

Department of Computer Engineering and Information Technology

References

Ricci F, Rokach L, Shapira B. Introduction to recommender systems handbook. Springer US, 2011.

López-Nores M, Blanco-Fernández Y, Pazos-Arias JJ, Díaz-Redondo RP. Property-based collaborative filtering: A new paradigm for semantics-based, health-aware recommender systems. 2010 5th International Workshop on Semantic Media Adaptation and Personalization (SMAP) 2010:98-103.

Blanco-Fernández Y, Pazos Arias JJ, Gil Solla A, Ramos Cabrer M, López Nores M, Barragáns Martínez B. AVATAR: Modeling users by dynamic ontologies in a TV recommender system based on semantic reasoning. 3th European Conference on Interactive TV 2005:173-181.

De Dombal FT, Leaper DJ, Horrocks JC, Staniland JR, McCann AP. Human and computer-aided diagnosis of abdominal pain: further report with emphasis on performance of clinicians. British medical journal 1974;1(5904):376.

Miller RA, Pople Jr HE, Myers JD. Internist-I, an experimental computer-based diagnostic consultant for general internal medicine. New England Journal of Medicine 1982;307(8):468-76.

Buchanan BG, Shortliffe EH. The MYCIN experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wasley 1984.

Kumar KA, Singh Y, Sanyal S. Hybrid approach using case-based reasoning and rule-based reasoning for domain independent clinical decision support in ICU. Expert Systems with Applications 2009; 36(1):65-71.

Lin H, Hsu YL, Hsu MS, Cheng CM. Development of a Telehealthcare Decision Support System for Patients Discharged from the Hospital. Telemedicine and e-Health 2014;20(8):748-56.

Michalowski W, Slowinski R, Wilk S, Farion KJ, Pike J, Rubin S. Design and development of a mobile system for supporting emergency triage. Methods of Information in Medicine-Methodik der Information in der Medizin 2005;44(1):14-24.

Farion K, Michalowski W, Wilk S, O'Sullivan DM, Rubin S, Weiss D. Clinical decision support system for point of care use: ontology driven design and software implementation. Methods of information in medicine 2009;48(4):381-90.

Shaban-Nejad A, Riazanov A, Charland KM, Rose GW, Baker CJ, Tamblyn R, Forster AJ, Buckeridge DL. HAIKU: a semantic framework for surveillance of healthcare-associated infections. Procedia Computer Science 2012;10:1073-9.

Bertaud-Gounot V, Duvauferrier R, Burgun A. Ontology and medical diagnosis. Informatics for Health and Social Care 2012;37(2):51-61.

Schriml LM, Arze C, Nadendla S, Chang YW, Mazaitis M, Felix V, Feng G, Kibbe WA. Disease Ontology: a backbone for disease semantic integration. Nucleic acids research. 2012; 40(D1):D940-6.

Bousquet C, Sadou É, Souvignet J, Jaulent MC, Declerck G. Formalizing MedDRA to support semantic reasoning on adverse drug reaction terms. Journal of biomedical informatics 2014;49:282-91.

Valls A, Gibert K, Sánchez D, Batet M. Using ontologies for structuring organizational knowledge in Home Care assistance. International Journal of Medical Informatics 2010;79(5):370-87.

Riaño D, Real F, López-Vallverdú JA, Campana F, Ercolani S, Mecocci P, Annicchiarico R, Caltagirone C. An ontology-based personalization of health-care knowledge to support clinical decisions for chronically ill patients. Journal of biomedical informatics 2012;45(3):429-46.

Campana F, RMB C, Cerracchio E, Annicchiarico R, Lucia IS, Federici A. Knowledge-Based HomeCare eServices for an Ageing Europe. Technical Report; [cited at 2017 March]. Available from: URL: www.pdfs.semanticscholar.org.

García-Crespo Á, Rodríguez A, Mencke M, Gómez-Berbís JM, Colomo-Palacios R. ODDIN: Ontology-driven differential diagnosis based on logical inference and probabilistic refinements. Expert Systems with Applications 2010;37(3):2621-8.

Mohammed O, Benlamri R, Fong S. Building a diseases symptoms ontology for medical diagnosis: an integrative approach. 2012 International Conference on Future Generation Communication Technology (FGCT): IEEE. 2012:104-108.

Sanaeifar A, Farahi A, Tara M. SEPHYRES 1: A Symptom Checker based on Semantic Pain Descriptors and Weight Spreading. Applied Medical Informatics 2016;38(3-4):105-116.

Isabel Engine. [cited 2016 Oct]. Available from: URL: www.Patient.info.

WebMD. [cited 2017 Jan]. Available from: URL: www.symptoms.webmd.com.

Crestani F. Application of Spreading Activation Techniques in Information Retrieval. Artificial Intelligence Review 1997;11(6):453-482.

Blanco-Fernández Y, Pazos-Arias JJ, Gil-Solla A, Ramos-Cabrer M, López-Nores M. Semantic reasoning: A path to new possibilities of personalization. European Semantic Web Conference, Springer Berlin Heidelberg; 2008. p. 720-735.

Blanco-Fernández Y, López-Nores M, Gil-Solla A, Ramos-Cabrer M, Pazos-Arias JJ. Exploring synergies between content-based filtering and spreading activation techniques in knowledge-based recommender systems. Information Sciences 2011;181(21):4823-46.

Martín-Vicente MI, Gil-Solla A, Ramos-Cabrer M, Blanco-Fernandez Y, Lopez-Nores M. A semantic approach to avoiding fake neighborhoods in collaborative recommendation of coupons through digital TV. IEEE Transactions on Consumer Electronics 2010;56(1):54-62.

Downloads

Additional Files

Published

25.04.2017

How to Cite

1.
SANAEIFAR A, TARA M, AHADI M, BAHARI A, FARAAHI A. SEPHYRES: A Medical Diagnosis Model based on Semantic Pseudo-Fuzzy Plan and Radar-form Interface. Appl Med Inform [Internet]. 2017 Apr. 25 [cited 2024 Dec. 26];39(1-2):1-7. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/610

Issue

Section

Perspectives