Developing Inference Model to Diagnosis of Primary Immunodeficiency Diseases in Protégé

  • Fateme Sepehri ORCID Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran. AND Department of Health Information Technology, Mousavi Hospital, Zanjan University of Medical Sciences, Zanjan, Iran.
  • Mostafa Langarizadeh Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
  • Laleh Sharifi Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
  • Gholamreza Azizi Department of Laboratory Medicine, Imam Hassan Mojtaba Hospital, Alborz University of Medical Sciences, Karaj, Iran.
  • Reza Safdari Mail Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
  • Asghar Aghamohammadi Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran. AND Primary Immunodeficiency Diseases Network (PIDNeT), Universal Scientific Education and Research Network (USERN), Tehran, Iran.
Keywords:
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Abstract

Primary immunodeficiency diseases (PIDs) are a genetically  heterogeneous group disorders that affect distinct components of both humoral and cellular arms of the immune system (1,2). Overlapping signs and symptoms of these diseases is a challenge for diagnosis and treatment (3,4). Awareness of the  symptoms and considering   the   possibility   of   PID   in   differential diagnosis help to rapid recognition and more appropriate treatment   (2,5).   Timely   recognition   and   treatment reduced mortality and increased lifespan and quality of life of the patients (6). Memorization of all effective criteria to diagnosis is difficult, so developing a computerized program based on diagnosis criteria, improves significantly the quality of care (7,8).To develop the inference model to the diagnosis of PIDs, ontology has been used in this study. The study focused on eight common diseases of PIDs include Common Variable Immune Deficiency (CVID), X- Linked Agammaglobulinemia (Bruton’s) (XLA), Selective IgA Deficiency (SIgA), CD40L deficiency, UNG deficiency, Isolated immunoglobulin (Ig) G Subclass deficiency, Specific antibody deficiency (SAD) with normal Ig concentrations and normal numbers of B cells, Transient Hypogammaglobulinemia of infancy (THI) with normal numbers of B cells. Based on clinical guidelines  and   medical   literature   in   PID   (9),   we designed a checklist to extract and classified most important signs and symptoms, family history, and laboratory data for eight main type of primary antibody deficiencies   (PADs).   To   evaluate   the   quality   of checklist, data for 100 cases in a different type of PADs were tested. Using frame-based ontology modeling to create the inference model and "Noy and McGuinness" method to develop the inference model. "Noy and McGuinness" method includes seven stages (10). Below we describe each stage of the method:

References

Aghamohammadi A, Moghaddam ZG, Abolhassani H, Hallaji Z, Mortazavi H, Pourhamdi S, et al. Investigation of underlying primary immunodeficiencies in patients with severe atopic dermatitis. Allergologia et immunopathologia. 2014 Jul-Aug;42(4):336-41. PubMed PMID: 23735167.

Abolhassani H, Akbari F, Mirminachi B, Bazregari S, Hedayat E, Rezaei N, et al. Morbidity and mortality of Iranian patients with hyper IgM syndrome: a clinical analysis. Iranian journal of immunology : IJI. 2014 Jun;11(2):123-33. PubMed PMID: 24975969.

Abolhassani H, Mirminachi B, Daryabeigi M, Agharahimi Z, Aghamohammadi A, Rabbani A, et al. Evaluation of physicians' awareness of pediatric diseases in iran. Iranian journal of pediatrics. 2014 Feb;24(1):87-92. PubMed PMID: 25793051. Pubmed Central PMCID: 4359610.

Rezaei N, Mohammadinejad P, Aghamohammadi A. The demographics of primary immunodeficiency diseases across the unique ethnic groups in Iran, and approaches to diagnosis and treatment. Annals of the New York Academy of Sciences. 2011 Nov;1238:24-32. PubMed PMID: 22129050.

Azizi G, Abolhassani H, Asgardoon MH, Shaghaghi S, Negahdari B, Mohammadi J, et al. Managing patients with side effects and adverse events to immunoglobulin therapy. Expert review of clinical pharmacology. 2016;9(1):91-102. PubMed PMID: 26496172.

Abolhassani H, Hirbod-Mobarakeh A, Shahinpour S, Panahi M, Mohammadinejad P, Mirminachi B, et al. Mortality and morbidity in patients with X-linked agammaglobulinaemia. Allergologia et immunopathologia. 2015 Jan-Feb;43(1):62-6. PubMed PMID: 24485939.

Eslami V, Rouhani-Esfahani S, Hafezi-Nejad N, Refaeian F, Abdi S, Togha M. A computerized expert system for diagnosing primary headache based on International Classification of Headache Disorder (ICHD-II). SpringerPlus. 2013 Dec;2(1):199. PubMed PMID: 23710428. Pubmed Central PMCID: 3661080.

Abolhassani H, Aghamohammadi A, Pourjabbar S, Salehi Sadaghiani M, Nikayin S, Rabiee A, et al. Psychiatric aspects of primary immunodeficiency diseases: the parental study. Iranian journal of allergy, asthma, and immunology. 2013 Jun;12(2):176-81. PubMed PMID: 23754357.

Bonilla FA, Khan DA, Ballas ZK, Chinen J, Frank MM, Hsu JT, et al. Practice parameter for the diagnosis and management of primary immunodeficiency. The Journal of allergy and clinical immunology. 2015 Nov;136(5):1186-205 e1-78. PubMed PMID: 26371839.

Noy NF, McGuinness DL. Ontology development 101: A guide to creating your first ontology. Stanford knowledge systems laboratory technical report KSL-01-05 and Stanford medical informatics technical report SMI-2001-0880; 2001.

Shadgar B, Osare A, HaratianNejadi A. Semantic Web- Concepts and techniques. Tehtan: Armaghan; 2014. [in persian]

SanatJoo A, Fathian A. The methodology used in the design, construction and implementation of ontology, approaches, languages and tools in the field of library and information science ASFAONT (case study design ontology). National studies on librarianship and information. 2012;15(57):29. [in persian]

Published
2017-05-16
How to Cite
1.
Sepehri F, Langarizadeh M, Sharifi L, Azizi G, Safdari R, Aghamohammadi A. Developing Inference Model to Diagnosis of Primary Immunodeficiency Diseases in Protégé. Acta Med Iran. 55(4):280-281.
Section
Letter to the Editor