An ontology-based framework aiming to support personalized exercise prescription: Application in cardiac rehabilitation

Κωστόπουλος, Κωνσταντίνος; Chouvarda, Ioanna; Koutkias, Vassilis; Kokonozi, Athina; Gils, Mark van; Maglaveras, Nicos

doi:10.1109/iembs.2011.6090456

Cited by 15 publications

(6 citation statements)

References 6 publications

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“…Clinical ontologies are increasingly used as a means for improving various aspects of health care 68–70 . CDS is one such area in medicine in which clinical ontologies are being used to develop more efficient and accurate systems.…”

Section: Discussionmentioning

confidence: 99%

Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis

Dissanayake

Colicchio

Cimino

2019

Journal of the American Medical Informatics Association

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Objective The study sought to describe the literature describing clinical reasoning ontology (CRO)–based clinical decision support systems (CDSSs) and identify and classify the medical knowledge and reasoning concepts and their properties within these ontologies to guide future research. Methods MEDLINE, Scopus, and Google Scholar were searched through January 30, 2019, for studies describing CRO-based CDSSs. Articles that explored the development or application of CROs or terminology were selected. Eligible articles were assessed for quality features of both CDSSs and CROs to determine the current practices. We then compiled concepts and properties used within the articles. Results We included 38 CRO-based CDSSs for the analysis. Diversity of the purpose and scope of their ontologies was seen, with a variety of knowledge sources were used for ontology development. We found 126 unique medical knowledge concepts, 38 unique reasoning concepts, and 240 unique properties (137 relationships and 103 attributes). Although there is a great diversity among the terms used across CROs, there is a significant overlap based on their descriptions. Only 5 studies described high quality assessment. Conclusion We identified current practices used in CRO development and provided lists of medical knowledge concepts, reasoning concepts, and properties (relationships and attributes) used by CRO-based CDSSs. CRO developers reason that the inclusion of concepts used by clinicians’ during medical decision making has the potential to improve CDSS performance. However, at present, few CROs have been used for CDSSs, and high-quality studies describing CROs are sparse. Further research is required in developing high-quality CDSSs based on CROs.

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Section: Discussionmentioning

confidence: 99%

Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis

Dissanayake

Colicchio

Cimino

2019

Journal of the American Medical Informatics Association

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“…Further efforts have been made with regard to artificial intelligence-based exercise prescription. [135][136][137][138][139] Most of these studies describe a framework to automate exercise prescription based on patient demographics, comorbidities, test results and reason for referral. Randomised clinical trials evaluating fully computerised exercise prescription are still lacking.…”

Section: Impact Of 'Big Data' and Artificial Intelligence On Translatmentioning

confidence: 99%

Towards a personalised approach in exercise-based cardiovascular rehabilitation: How can translational research help? A ‘call to action’ from the Section on Secondary Prevention and Cardiac Rehabilitation of the European Association of Preventive Cardiology

Gevaert

Adams

Bahls

et al. 2019

Eur J Prev Cardiolog

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The benefit of regular physical activity and exercise training for the prevention of cardiovascular and metabolic diseases is undisputed. Many molecular mechanisms mediating exercise effects have been deciphered. Personalised exercise prescription can help patients in achieving their individual greatest benefit from an exercise-based cardiovascular rehabilitation programme. Yet, we still struggle to provide truly personalised exercise prescriptions to our patients. In this position paper, we address novel basic and translational research concepts that can help us understand the principles underlying the inter-individual differences in the response to exercise, and identify early on who would most likely benefit from which exercise intervention. This includes hereditary, non-hereditary and sex-specific concepts. Recent insights have helped us to take on a more holistic view, integrating exercise-mediated molecular mechanisms with those influenced by metabolism and immunity. Unfortunately, while the outline is recognisable, many details are still lacking to turn the understanding of a concept into a roadmap ready to be used in clinical routine. This position paper therefore also investigates perspectives on how the advent of ‘big data’ and the use of animal models could help unravel inter-individual responses to exercise parameters and thus influence hypothesis-building for translational research in exercise-based cardiovascular rehabilitation.

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“…In the domain of biomedicine, there have been a large number of domain semantic knowledge bases built on ontologies [8], such as gene ontology [9], human phenotype ontology [10], and disease ontology [11]. Correspondingly, in the domain of health care, a large number of aided diagnosis research [1], [12]- [14] and other applied research [15]- [17] have also appeared based on domain semantic knowledge bases. These aided diagnosis methods of diseases based on the domain semantic knowledge bases can quickly support the diagnosis of a large number of common diseases.…”

Section: Introductionmentioning

confidence: 99%

Research on the Aided Diagnosis Method of Diseases Based on Domain Semantic Knowledge Bases

2024

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The health care domain is a knowledge-intensive domain. The quality of clinical diagnosis relies mainly on the medical knowledge and experience held by doctors. However, the ability of a single doctor is very limited, so the quality of clinical diagnosis is currently not high. In this paper, an aided diagnosis method based on domain semantic knowledge bases is proposed. Firstly, a domain semantic knowledge base is established by extracting and refining the knowledge of the medicine subject matter domain from the Freebase RDF dumps. Then, based on the semantic knowledge base, the algorithms for calculating the weights of the symptoms in the knowledge base, the relative weights of the diseases related to the input symptom set from a patient, and the related symptom set related to the input symptom set from the patient are proposed. Finally, the clinical medical record data of several common diseases are selected to make an evaluation on the proposed method. For each medical record, the symptom information is extracted from the chief complaint as the patient's input symptom set. Based on the input symptom set, the method of this paper is used to obtain the list of related diseases and the ranking of disease relative weights. From the disease relevance rankings, the Top 1 (first diagnosis) and Top-3 (first 3 diagnoses) are compared with the doctor's diagnoses in the medical records. Among them, ovarian cyst has the highest Top-1 and Top-3 hit rates of 67.3% and 89.1%, respectively. Followed by acute upper respiratory tract infection, Top-1 and Top-3 hit rates are 56.6% and 85.2%, respectively. The average Top-1 and Top-3 hit rates are 47.9% and 79.7%, respectively. Compared with the relevant methods, the method of this paper is better. The evaluation results show that based on the domain semantic knowledge base and the aided diagnosis method of diseases constructed in this paper, it is possible to provide aided diagnosis services of a large number of common diseases for general practitioners (especially inexperienced doctors) at the grassroots level as well as selfdiagnosis services of diseases for patients.

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An ontology-based framework aiming to support personalized exercise prescription: Application in cardiac rehabilitation

Cited by 15 publications

References 6 publications

Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis

Using clinical reasoning ontologies to make smarter clinical decision support systems: a systematic review and data synthesis

Towards a personalised approach in exercise-based cardiovascular rehabilitation: How can translational research help? A ‘call to action’ from the Section on Secondary Prevention and Cardiac Rehabilitation of the European Association of Preventive Cardiology

Research on the Aided Diagnosis Method of Diseases Based on Domain Semantic Knowledge Bases

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