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Interoperability between Heterogeneous Process Workflows using Interaction Ontology
Wajahat Ali Khan,Muhammad Bilal Amin,Sungyoung Lee,Young Koo Lee 한국정보과학회 2011 한국정보과학회 학술발표논문집 Vol.38 No.1C
Heterogeneity in different Health Information Systems (HIS) processes persists to be the most demanded problem to be resolved in healthcare domain. The only way to resolve this problem is to practice health standards. One of such standards is Health Level Seven (HL7), used for the communication of medical information between healthcare systems. HL7 V3 has the aim to support all healthcare workflows. It defines series of electronic messages called interactions to support healthcare workflows. These interactions are part of the Interaction Model. Different healthcare organizations can conform to different process workflows based on their requirements. The heterogeneity in workflows results in communication blockade between sender and receiver healthcare organizations. We propose Interaction Ontology in order to cater the heterogeneity in workflows and provide process interoperability.
Object-oriented and ontology-alignment patterns-based expressive Mediation Bridge Ontology (MBO)
Khan, Wajahat Ali,Amin, Muhammad Bilal,Khattak, Asad Masood,Hussain, Maqbool,Afzal, Muhammad,Lee, Sungyoung,Kim, Eun Soo SAGE Publications 2015 JOURNAL OF INFORMATION SCIENCE Vol.41 No.3
<P>The Semantic Web is dependent on extensive knowledge management by interlinking resources on the web using matching techniques. This role is played by the progressing domain of ontology matching, by introducing ontology-matching tools. The focus of these matching tools is limited to matching techniques and automation, rather than expressive formal representation of alignments. We propose Mediation Bridge Ontology (MBO), an expressive alignment representation ontology used to store correspondences between matching ontologies matched by our ontology-matching tool, System for Parallel Heterogeneity Resolution (SPHeRe). The MBO utilizes object-oriented design patterns and the proposed ontology-alignment design patterns to provide extendibility and reusability factors to SPHeRe system. We compared our proposed system with existing systems using Coupling Factor, Number of Polymorphic methods and Rate of Change metrics to support extendibility and reusability. These factors contribute to the overall objective of interoperability for knowledge management in the Semantic Web.</P>
상호교류 헬스케어시스템을 위한 사용자정의 온톨로지 매핑
와자하트알리칸 ( Wajahat Ali Khan ),마크불후세인 ( Maqbool Hussain ),무하마드아프잘 ( Muhammad Afzal ),이승룡 ( Sungyoung Lee ),정태충 ( Tae Choong Chung ) 한국정보처리학회 2013 한국정보처리학회 학술대회논문집 Vol.20 No.1
Accuracy of mappings is the key for achieving true interoperability among different healthcare systems. The initial step towards interoperable healthcare systems is compliancy with healthcare standards (HL7, openEHR, CEN 13606). Ontologies for these standards are developed that require ontology matching to generate generalized ontology mappings. Organizations conform to specific concepts of different standards based on their requirements. This step is called as conformance claims and is based on Personalized-Detailed Clinical Model. It invalidates some of the generalized mappings because of non-conformed concepts and leads to the necessity of the proposed technique of customized ontology mappings. These customized ontology mappings compliment the generalized ontology mapping to increase the level of accuracy of mappings and thus achieving data interoperability. The proposed system ensures quality of care to patients by timely delivery of healthcare information.
와자하트알리칸 ( Wajahat Ali Khan ),마크불후세인 ( Maqbool Hussain ),아사드마수드카탁 ( Asad Masood Khattak ),이승룡 ( Sungyoung Lee ),구교호 ( Young Koo Lee ) 한국정보처리학회 2011 한국정보처리학회 학술대회논문집 Vol.18 No.1
Due to heterogeneity in Data and Processes, healthcare systems are facing the challenge of interoperability. This heterogeneity results in different healthcare workflows of each individual organization. The compatibility of these heterogeneous workflows is possible when standards are followed. HL7 is one of the standards that is used for communicating medical data between healthcare systems. Its newer version V3 is providing semantic interoperability which is lacking in V2. The interoperability in HL7 V3 is only limited to data level and process level interoperability needs to be catered. The process level interoperability is achieved only when heterogeneous workflows are aligned. These workflows are very complex in nature due to continuous change in medical data resulting in problems related to maintenance and degree of automation. Semantic technologies plays important role in resolving the above mentioned problems. This research work is based on the integration of semantic technology in HL7 V3 standard to achieve semantic process interoperability. Web Service Modeling Framework (WSMF) is used for incorporating semantics in HL7 V3 processes and achieves seamless communication. Interaction Ontology represents the process artifacts of HL7 V3 and helps in achieving automation.
Personalization of wellness recommendations using contextual interpretation
Afzal, Muhammad,Ali, Syed Imran,Ali, Rahman,Hussain, Maqbool,Ali, Taqdir,Khan, Wajahat Ali,Amin, Muhammad Bilal,Kang, Byeong Ho,Lee, Sungyoung Elsevier 2018 expert systems with applications Vol.96 No.-
<P><B>Abstract</B></P> <P>A huge array of personalized healthcare and wellness systems are introduced into the portfolio of digital health and quantified-self movement in recent years. These systems share common capabilities including self-tracking/monitoring and self-quantifications, based on the raw sensory data. These capabilities provide solid ground for the users to be more aware of their health; however, such measures are inefficient for changing the unhealthy habits of the users. In order to induce healthy habits in the users, a system must be capable of generating context-aware personalized recommendations. The main obstacle in this regard is the contextual interpretation of recommendations based on user's current context and contextual preferences. To resolve these issues, we propose a methodology of cross-context interpretation of recommendations (CCIR) for personalized health and wellness services. The CCIR method adds additional capabilities to the traditional reasoning methods and builds advanced form of the reasoning with the incorporation of contextual factors in the process of interpretations of the recommendations. With CCIR, the self-quantification systems can be enhanced to generate personalized recommendations in addition to tracking, quantifying, and monitoring user activities. In order to validate the proposed CCIR methodology, a set of 40 contextual scenarios and corresponding recommendations are presented for the evaluation collected from 40 different end users and 10 domain experts. Using chi-square test evaluation, the results demonstrated acceptable “goodness of fit” indices for the system developed on proposed CCIR methodology with respect to the end users’ opinion. Also from the statistical observation, it is found that there exists a higher level agreement towards the system between the participants of both end users and experts.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A method for cross-context interpretations of health and wellness recommendations. </LI> <LI> A mechanism of refining generalized recommendations to personalized recommendations. </LI> <LI> The contextual interpretations are made for increasing the user acceptability of a system. </LI> </UL> </P>
Recommendations Service for Chronic Disease Patient in Multimodel Sensors Home Environment
Hussain, Maqbool,Ali, Taqdir,Khan, Wajahat Ali,Afzal, Muhammad,Lee, Sungyoung,Latif, Khalid Mary Ann Liebert 2015 TELEMEDICINE JOURNAL AND E HEALTH Vol.21 No.3
<P>With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC(3)). SC(3) services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC(3) platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms.</P>
Oresti Banos,Wajahat Ali Khan,Muha mmad Bilal Amin,허태호,방재훈,강동욱,Maqbool Hussain,Muhammad Afzal,Taqdir Ali,이승룡 한국통신학회 2015 정보와 통신 Vol.32 No.11
최근 의학 기술이 눈부시게 발전함에 따라 사람들은 수명이 연장되고 삶의 질 향상에 많은 관심을 가지게 되었다. 더욱이 혁신적인 디지털 기술 발전과 함께 다양한 웨어러블 기기와 수많은 헬스케어 어플리케이션이 출시되고 있으며, 이들은 어떻게 하면 개인의 성향이나 체질에 잘 맞는 맞춤형 (개인화) 서비스를 제공할 수 있을 것인가에 관심을 두고 진화하고 있다. 따라서 IoT 환경의 일상생활에서 입력되는 센서 데이터의 수집, 처리, 가공 기술, 일상 행위 및 라이프 스타일 인지, 지식 획득 및 관리 기술, 개인화 추천서비스 제공, 프라이버시 및 보안을 통합적으로 지원할 수 있는 프레임워크 개발에 대한 요구가 증대되고 있다. 이에 본 고에서는 저자가 개발중인 개인 맞춤 건강 및 웰니스 서비스를 제공하는 마이닝 마인즈 프레임워크를 소개한다. 마이닝 마인즈는 현존하는 최신 기술의 집약체로 개인화, 큐레이션, 빅 데이터 처리, 클라우드 컴퓨팅의 활용, 다양한 센서 정보의 수집과 분석, 진화형 지식의 생성과 관리, UI/UX를 통한 습관화 유도 등 다양한 요소를 포함한다. 그리고 건강 및 웰니스 프레임워크 요구사항 분석을 통해 마이닝 마인즈가 이러한 요구를 충족시킬 수 있으며, 개발된 프로토타입을 통해 개인화 서비스의 발전 가능성을 입증하고 향후 나아가야 할 방향을 제시한다.