Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach

Verma, Anju; Fiasché, Maurizio; Cuzzola, Maria; Iacopino, Pasquale; Morabito, Francesco Carlo; Kasabov, Nikola

doi:10.1007/978-3-642-10684-2_40

Cited by 11 publications

(7 citation statements)

References 15 publications

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“…14,15 The main objective of personalized modeling is to create a model for each patient (sample), which is able to reveal the most important information specifically for each sample, focusing attention on the individual patient (sample) rather than simply on the global problem space. 16,17 Previous works have reported that personalized modeling can produce better classification results than those obtained from classical global modeling, 14,16,18 making it more appropriate to build clinical decision support systems for new patients. The framework proposed by Fiasché et al 11,19 used a "personalized" wrapping method, a PMGS described in detail in recent papers 20,21 for gene expression data analysis, integrating new data with the existing models; the block diagram is reported in Figure 1.…”

Section: Personalized Modeling For Identification Of Target Genes In mentioning

confidence: 99%

A molecular and computational diagnostic approach identifies FOXP3, ICOS, CD52 and CASP1 as the most informative biomarkers in acute graft-versus-host disease

Cuzzola¹,

Fiasché²,

Iacopino

et al. 2012

Haematologica

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The online version of this article has a Supplementary Appendix. BackgroundAcute graft-versus-host disease is a severe complication of allogeneic stem cell transplantation in which the functional immune cells of the donor recognize the recipient as foreign and mount an immunological attack. There is an urgent need for better diagnostic instruments for the assessment of acute graft-versus-host disease. In the present study, a novel bioinformatics framework was used to identify gene expression patterns associated with acute graft-versushost disease in patients undergoing allogeneic hematopoietic stem cell transplantation. Design and MethodsPeripheral blood cells were collected prospectively from patients who did develop acute graftversus-host disease (YES) and from those who did not (NO). Gene expression profiling was performed using a panel of 47 candidate genes potentially involved in alloreactive responses. The entire population of YES/NO acute graft-versus-host disease patients formed the experimental validation set. Personalized modeling based on a gene selection technique was applied to identify the most significant mRNA transcripts, which were then used to profile individual data samples for training and testing the classification/prediction framework. ResultsA leave-one-out cross-validation procedure was performed to investigate the robustness of the classification framework producing the following results: 100% on the training dataset and 97% on the testing dataset. According to our integrated methodology, transcripts for FOXP3, ICOS, CD52 and CASP1, genes involved in immune alloreactive responses and participating in immune cell interactions, were identified as the most informative biomarkers in allogeneic stem cell transplant recipients experiencing acute graft-versus-host disease. ConclusionsThis study demonstrates that the integrated methodology proposed is useful for the selection of valid gene targets for the diagnosis of acute graft-versus-host disease, producing satisfactory accuracy over independent clinical features of the allogeneic transplanted population.

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Section: Personalized Modeling For Identification Of Target Genes In mentioning

confidence: 99%

A molecular and computational diagnostic approach identifies FOXP3, ICOS, CD52 and CASP1 as the most informative biomarkers in acute graft-versus-host disease

Cuzzola¹,

Fiasché²,

Iacopino

et al. 2012

Haematologica

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“…The noise information in the global problem space should be excluded to obtain a satisfactory result from the analysis. As discussed by Song and Kasabov (2006) and Verma et al (2009), personalized modeling focuses on the individual sample rather than simply on the global problem space, so that creating a personalized problem space specifically for the new data can be a more appropriate solution to analyze new coming data sample in medical area. Personalized modeling is a relative new method in bioinformatics research, which is less found in literature.…”

Section: Gene Selection Methods and Personalized Modelingmentioning

confidence: 99%

Advances in medical decision support systems for diagnosis of acute graft-versus-host disease: molecular and computational intelligence joint approaches

Fiasché

Cuzzola²,

Irrera³

et al. 2011

Front. Biol.

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Acute graft-versus-host disease (aGVHD) is a serious systemic complication of allogeneic hematopoietic stem cell transplantation (HSCT) causing considerable morbidity and mortality. Acute GVHD occurs when alloreactive donor-derived T cells recognize host-recipient antigens as foreign. These trigger a complex multiphase process that ultimately results in apoptotic injury in target organs. The early events leading to GVHD seem to occur very soon, presumably within hours from the graft infusion. Therefore, when the first signs of aGVHD clinically manifest, the disease has been ongoing for several days at the cellular level, and the inflammatory cytokine cascade is fully activated. So, it comes as no surprise that progress in treatment based on clinical diagnosis of aGVHD has been limited in the past 30 years. It is likely that a pre-emptive strategy using systemic high-dose corticosteroids as early as possible could improve the outcome of aGVHD. Due to the deleterious effects of such treatment particularly in terms of infection risk posed by systemic steroid administration in a population that is already immune-suppressed, it is critical to identify biomarker signatures for approaching this very complex task. Some research groups have begun addressing this issue through molecular and proteomic analyses, combining these approaches with computational intelligence techniques, with the specific aim of facilitating the identification of diagnostic biomarkers in aGVHD. In this review, we focus on the aGVHD scenario and on the more recent state-of-the-art. We also attempt to give an overview of the classical and novel techniques proposed as medical decision support system for the diagnosis of GVHD.

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“…Ontologies focused on health care are prolific in number and scope, yet are relatively limited in their impact on such a large multifaceted domain. Computer ontologies have been developed and some adopted by medical professionals, with a notable bias in the published research towards provider-centric systems needs (Amoussou, 2011;Beveridge and Fox, 2006;Cenan et al, 2008;Chalortham et al, 2009;Ganendran et al, 2002;Kim and Song, 2007;Kumar and Smith, 2003;Kumar et al, 2004a;Lin and Sakamoto, 2009;Mabotuwana and Warren, 2009;Noy et al, 2009;Bickmore et al, 2011;Rector, 2008;Shahar et al, 2004;Smith et al, 2007) compared with the patientpractitioner relationship environment (Ahmed, 2011;Bailin and Lehmann, 2003;Barrett, 2006;Verma et al, 2009). Context-based task ontologies (CTOs) have been created by Kumar et al to form a core component of a Computer Interpretable Guideline Model intended to automate representation and execution of clinical practice guidelines (CPGs) (Kumar et al, 2004b).…”

Section: Itp 292mentioning

confidence: 99%

Ontology based intercultural patient practitioner assistive communications from qualitative gap analysis

Forbes

Wongthongtham

2016

Information Technology &Amp; People

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Purpose – There is an increasing interest in using information and communication technologies to support health services. But the adoption and development of even basic ICT communications services in many health services is limited, leaving enormous gaps in the broad understanding of its role in health care delivery. The purpose of this paper is to address a specific (intercultural) area of healthcare communications consumer disadvantage; and it examines the potential for ICT exploitation through the lens of a conceptual framework. The opportunity to pursue a new solutions pathway has been amplified in recent times through the development of computer-based ontologies and the resultant knowledge from ontologist activity and consequential research publishing. Design/methodology/approach – A specific intercultural area of patient disadvantage arises from variations in meaning and understanding of patient and clinician words, phrases and non-verbal expression. Collection and localization of data concepts, their attributes and individual instances were gathered from an Aboriginal trainee nurse focus group and from a qualitative gap analysis (QGA) of 130 criteria-selected sources of literature. These concepts, their relationships and semantic interpretations populate the computer ontology. The ontology mapping involves two domains, namely, Aboriginal English (AE) and Type II diabetes care guidelines. This is preparatory to development of the Patient Practitioner Assistive Communications (PPAC) system for Aboriginal rural and remote patient primary care. Findings – The combined QGA and focus group output reported has served to illustrate the call for three important drivers of change. First, there is no evidence to contradict the hypothesis that patient-practitioner interview encounters for many Australian Aboriginal patients and wellbeing outcomes are unsatisfactory at best. Second, there is a potent need for cultural competence knowledge and practice uptake on the part of health care providers; and third, the key contributory component to determine success or failures within healthcare for ethnic minorities is communication. Communication, however, can only be of value in health care if in practice it supports shared cognition; and mutual cognition is rarely achievable when biopsychosocial and other cultural worldview differences go unchallenged. Research limitations/implications – There has been no direct engagement with remote Aboriginal communities in this work to date. The authors have initially been able to rely upon a cohort of both Indigenous and non-Indigenous people with relevant cultural expertise and extended family relationships. Among these advisers are health care practitioners, academics, trainers, Aboriginal education researchers and workshop attendees. It must therefore be acknowledged that as is the case with the QGA, the majority of the concept data is from third parties. The authors have also discovered that urban influences and cultural sensitivities tend to reduce the extent of, and opportunity to, witness AE usage, thereby limiting the ability to capture more examples of code-switching. Although the PPAC system concept is qualitatively well developed, pending future work planned for rural and remote community engagement the authors presently regard the work as mostly allied to a hypothesis on ontology-driven communications. The concept data population of the AE home talk/health talk ontology has not yet reached a quantitative critical mass to justify application design model engineering and real-world testing. Originality/value – Computer ontologies avail us of the opportunity to use assistive communications technology applications as a dynamic support system to elevate the pragmatic experience of health care consultations for both patients and practitioners. The human-machine interactive development and use of such applications is required just to keep pace with increasing demand for healthcare and the growing health knowledge transfer environment. In an age when the worldwide web, communications devices and social media avail us of opportunities to confront the barriers described the authors have begun the first construction of a merged schema for two domains that already have a seemingly intractable negative connection. Through the ontology discipline of building syntactically and semantically robust and accessible concepts; explicit conceptual relationships; and annotative context-oriented guidance; the authors are working towards addressing health literacy and wellbeing outcome deficiencies of benefit to the broader communities of disadvantage patients.

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Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach

Cited by 11 publications

References 15 publications

A molecular and computational diagnostic approach identifies FOXP3, ICOS, CD52 and CASP1 as the most informative biomarkers in acute graft-versus-host disease

A molecular and computational diagnostic approach identifies FOXP3, ICOS, CD52 and CASP1 as the most informative biomarkers in acute graft-versus-host disease

Advances in medical decision support systems for diagnosis of acute graft-versus-host disease: molecular and computational intelligence joint approaches

Ontology based intercultural patient practitioner assistive communications from qualitative gap analysis

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