シカク ショウガイシャ ヘ ノ シンキュウ キョウイク ニ オケル オントロジー ベース キョウザイ ノ ユウコウセイ

我々は視覚障害者向けの鍼灸、特に経絡と経穴に関する教育材料の研究に取り組んだ。この教材では、鍼灸分野における概念間の関係の体系的な理解を可能にすべく、オントロジーを用いた。オントロジーの概念図によりオントロジー教材を作成し、これを鍼灸の講義で使用した群とオントロジー教材未使用群とで経絡・経穴の試験の結果を比較し、その有効性を解析した。その結果、オントロジー教材を使用した学生の経絡・経穴の試験の得点は、オントロジー教材未使用群の学生の得点よりも有意(P < 0.001)に高く、経絡と経穴の学習にオントロジー教材有効である事が明らかになった。この結果は、オントロジーの視覚障害者教育への利用が視覚障害者の鍼灸理論の学習へも有効であることを示唆している。In this study we developed learning material of acupuncture - acupoints and meridians - for visually impaired people. For this learning material, we used ontology to construct the relations between the concepts in the acupuncture and moxibustion field which also enables tactical understanding similarly as visual understanding. We then used our learning material in the acupuncture lecture for the visually impaired students, and quantitatively analysed its efficacy to compare the results with the group which did not use the learning material. As a result, the students, who used our learning material, scored significantly higher in the examination than the students of non-use group (P < 0.001), suggesting that our learning material was effective for learning of acupuncture theory

Expression model for multiple relationships in the ontology of traditional Chinese medicine knowledge

AbstractObjectiveTo explore multiple relationships in traditional Chinese medicine (TCM) knowledge by comparing binary and multiple relationships during knowledge organization.MethodsCharacteristics of binary and multiple semantic relationships as well as their associations are described. A method to classify multiple relationships based on the involvement of time is proposed and theoretically validated using examples from the ancient TCM classic Important Formulas Worth a Thousand Gold Pieces. The classification includes parallel multiple relationships, restricted multiple relationships, multiple relationships that involve time, and multiple relationships that involve time restriction. Next, construction of multiple semantic relationships for TCM concepts in each classification using Protégé, an ontology editing tool is described.ResultsProtégé is superior to a binary relationship and less than ideal with multiple relationships during the constitution of concept relationships.ConclusionWhen applied in TCM, the semantic relationships constructed by Protégé are superior than those constructed by correlation and/or attribute relationships, but less ideal than those constructed by the human cognitive process

Doctor of Philosophy

dissertationThe use of the various complementary and alternative medicine (CAM) modalities for the management of chronic illnesses is widespread, and still on the rise. Unfortunately, tools to support consumers in seeking information on the efficacy of these treatments are sparse and incomplete. The goals of this work were to understand CAM information needs in acquiring CAM information, assess currently available information resources, and investigate informatics methods to provide a foundation for the development of CAM information resources. This dissertation consists of four studies. The first was a quantitative study that aimed to assess the feasibility of delivering CAM-drug interaction information through a web-based application. This study resulted in an 85% participation rate and 33% of those patients reported the use of CAMs that had potential interactions with their conventional treatments. The next study aimed to assess online CAM information resources that provide information on drug-herb interactions to consumers. None of the sites scored high on the combination of completeness and accuracy and all sites were beyond the recommended reading level per the US Department of Health and Human Services. The third study investigated information-seeking behaviors for CAM information using an existing cohort of cancer survivors. The study showed that patients in the cohort continued to use CAM well into survivorship. Patients felt very much on their own in dealing with issues outside of direct treatment, which often resulted in a search for options and CAM use. Finally, a study was conducted to investigate two methods to semi-automatically extract CAM treatment relations from the biomedical literature. The methods rely on a database (SemMedDB) of semantic relations extracted from PubMed abstracts. This study demonstrated that SemMedDB can be used to reduce manual efforts, but review of the extracted sentences is still necessary due to a low mean precision of 23.7% and 26.4%. In summary, this dissertation provided greater insight into consumer information needs for CAM. Our findings provide an opportunity to leverage existing resources to improve the information-seeking experience for consumers through high-quality online tools, potentially moving them beyond the reliance on anecdotal evidence in the decision-making process for CAM

Semantic Web for data harmonization in Chinese medicine

Scientific studies to investigate Chinese medicine with Western medicine have been generating a large amount of data to be shared preferably under a global data standard. This article provides an overview of Semantic Web and identifies some representative Semantic Web applications in Chinese medicine. Semantic Web is proposed as a standard for representing Chinese medicine data and facilitating their integration with Western medicine data

Epistemic cultures in complementary medicine: knowledge-making in university departments of osteopathy and Chinese medicine

© 2016 Informa UK Limited, trading as Taylor & Francis Group. There is increasing pressure on complementary and alternative medicine (CAM) to follow the evidence-based approach promoted in allied health and medicine, in which the randomised control trial represents the evidence gold standard. However, many CAM advocates see these methods as undermining the holism of CAM practice. This paper explores how such tensions are managed in CAM university departments – settings in which particular forms of knowledge and evidence are given ‘official’ imprimatur by CAM educators and researchers. By comparing two types of CAM, the paper also unpacks differences within this broad category, asking whether CAM academic disciplines comprise different ‘epistemic cultures’ (Knorr-Cetina, K. (1999). Epistemic cultures: How the sciences make knowledge. Cambridge, MA: Harvard University Press). Interviews were conducted with 20 lecturers in Chinese medicine and osteopathy, across five Australian universities, and augmented with observation in two degree programs. Findings reveal contrasting ontological and epistemological perspectives between the two academic fields. Chinese medicine lecturers had largely adopted bioscientific models of research, typically conducting laboratory work and trials, although teaching included traditional theories. Osteopathy academics were more critical of dominant approaches and were focused on reframing notions of evidence to account for experiences, with some advocating qualitative research. The study illustrates CAM’s ‘epistemic disunity’ while also highlighting the particular challenges facing academic CAM

The BrainMap strategy for standardization, sharing, and meta-analysis of neuroimaging data

<p>Abstract</p> <p>Background</p> <p>Neuroimaging researchers have developed rigorous community data and metadata standards that encourage meta-analysis as a method for establishing robust and meaningful convergence of knowledge of human brain structure and function. Capitalizing on these standards, the BrainMap project offers databases, software applications, and other associated tools for supporting and promoting quantitative coordinate-based meta-analysis of the structural and functional neuroimaging literature.</p> <p>Findings</p> <p>In this report, we describe recent technical updates to the project and provide an educational description for performing meta-analyses in the BrainMap environment.</p> <p>Conclusions</p> <p>The BrainMap project will continue to evolve in response to the meta-analytic needs of biomedical researchers in the structural and functional neuroimaging communities. Future work on the BrainMap project regarding software and hardware advances are also discussed.</p

Boolean versus ranked querying for biomedical systematic reviews

Background: The process of constructing a systematic review, a document that compiles the published evidence pertaining to a specified medical topic, is intensely time-consuming, often taking a team of researchers over a year, with the identification of relevant published research comprising a substantial portion of the effort. The standard paradigm for this information-seeking task is to use Boolean search; however, this leaves the user(s) the requirement of examining every returned result. Further, our experience is that effective Boolean queries for this specific task are extremely difficult to formulate and typically require multiple iterations of refinement before being finalized. Methods: We explore the effectiveness of using ranked retrieval as compared to Boolean querying for the purpose of constructing a systematic review. We conduct a series of experiments involving ranked retrieval, using queries defined methodologically, in an effort to understand the practicalities of incorporating ranked retrieval into the systematic search task. Results: Our results show that ranked retrieval by itself is not viable for this search task requiring high recall. However, we describe a refinement of the standard Boolean search process and show that ranking within a Boolean result set can improve the overall search performance by providing early indication of the quality of the results, thereby speeding up the iterative query-refinement process. Conclusions: Outcomes of experiments suggest that an interactive query-development process using a hybrid ranked and Boolean retrieval system has the potential for significant time-savings over the current search process in the systematic reviewing

Clinical Decision Support System for Unani Medicine Practitioners

Like other fields of Traditional Medicines, Unani Medicines have been found as an effective medical practice for ages. It is still widely used in the subcontinent, particularly in Pakistan and India. However, Unani Medicines Practitioners are lacking modern IT applications in their everyday clinical practices. An Online Clinical Decision Support System may address this challenge to assist apprentice Unani Medicines practitioners in their diagnostic processes. The proposed system provides a web-based interface to enter the patient's symptoms, which are then automatically analyzed by our system to generate a list of probable diseases. The system allows practitioners to choose the most likely disease and inform patients about the associated treatment options remotely. The system consists of three modules: an Online Clinical Decision Support System, an Artificial Intelligence Inference Engine, and a comprehensive Unani Medicines Database. The system employs advanced AI techniques such as Decision Trees, Deep Learning, and Natural Language Processing. For system development, the project team used a technology stack that includes React, FastAPI, and MySQL. Data and functionality of the application is exposed using APIs for integration and extension with similar domain applications. The novelty of the project is that it addresses the challenge of diagnosing diseases accurately and efficiently in the context of Unani Medicines principles. By leveraging the power of technology, the proposed Clinical Decision Support System has the potential to ease access to healthcare services and information, reduce cost, boost practitioner and patient satisfaction, improve speed and accuracy of the diagnostic process, and provide effective treatments remotely. The application will be useful for Unani Medicines Practitioners, Patients, Government Drug Regulators, Software Developers, and Medical Researchers.Comment: 59 pages, 11 figures, Computer Science Bachelor's Thesis on use of Artificial Intelligence in Clinical Decision Support System for Unani Medicine

Towards Semantic e-Science for Traditional Chinese Medicine

<p>Abstract</p> <p>Background</p> <p>Recent advances in Web and information technologies with the increasing decentralization of organizational structures have resulted in massive amounts of information resources and domain-specific services in Traditional Chinese Medicine. The massive volume and diversity of information and services available have made it difficult to achieve seamless and interoperable e-Science for knowledge-intensive disciplines like TCM. Therefore, information integration and service coordination are two major challenges in e-Science for TCM. We still lack sophisticated approaches to integrate scientific data and services for TCM e-Science.</p> <p>Results</p> <p>We present a comprehensive approach to build dynamic and extendable e-Science applications for knowledge-intensive disciplines like TCM based on semantic and knowledge-based techniques. The semantic e-Science infrastructure for TCM supports large-scale database integration and service coordination in a virtual organization. We use domain ontologies to integrate TCM database resources and services in a semantic cyberspace and deliver a semantically superior experience including browsing, searching, querying and knowledge discovering to users. We have developed a collection of semantic-based toolkits to facilitate TCM scientists and researchers in information sharing and collaborative research.</p> <p>Conclusion</p> <p>Semantic and knowledge-based techniques are suitable to knowledge-intensive disciplines like TCM. It's possible to build on-demand e-Science system for TCM based on existing semantic and knowledge-based techniques. The presented approach in the paper integrates heterogeneous distributed TCM databases and services, and provides scientists with semantically superior experience to support collaborative research in TCM discipline.</p