Dr Tejal Shah
- Email: firstname.lastname@example.org
- Telephone: +44 (0) 191 208 4702
- Address: The Core
Newcastle upon Tyne
Tejal is a Research Associate in the Data to Knowledge (D2K) research group working primarily on the Connected Health Cities (CHC) programme.
Tejal practised clinical dentistry for several years before pursuing Health Informatics when she also worked as a research assistant in the School of Information Technologies at the University of Sydney (USyd). She was involved in the development of clinical information management and trauma registry information systems at USyd.
PhD: UNSW Sydney, Australia, 2016
Master of Health Informatics: University of Sydney, Australia, 2012
Bachelor of Dental Surgery: Government Dental College and Hospital, Mumbai, India, 2005
Tejal's current research focus is on the understanding, development, and application of Semantic Web technologies such as ontologies, semantic rules, and queries to address the problems of complex data representation, management, and analysis in the biomedical domain.
Tejal is responsible for developing and implementing consent/preferences metadata in the CHC's trusted research environment platform to ensure authorised access to data. She is also working on developing tools and techniques for scalable, semantic harmonisation and integration of heterogeneous biomedical data for research.
Tejal is also involved in the implementation of SNOMED CT at the Newcastle upon Tyne Hospitals NHS Foundation Trust (NuTH) where she advises on the theretical aspects of the terminology as well as lends practical support for clinical coding using SNOMED CT. Further, she works with clinical staff and the IT and clinical coding teams to understand the perspectives of end-users towards the use of SNOMED CT and identify difficulties that are then used to design improvements to the user interface.
- Data harmonisation and integration
- Clinical terminologies and ontologies
- Ontology patterns
- Description Logic and Web Ontology Language
- Knowledge representation and reasoning
- Clinical decision support systems
A list of publications can be found on:
- Garg S, Aryal J, Wang H, Shah T, Kecskemeti G, Ranjan R. Cloud computing based bushfire prediction for cyber-physical emergency applications. Future Generation Computer Systems 2018, 79(1), 354-363.
- Sun S, Song W, Zomaya AY, Xiang Y, Choo KKR, Shah T, Wang L. Associative retrieval in spatial big data based on spreading activation with semantic technology. Future Generation Computer Systems 2016, 76, 499-509.
- Shah T, Yavari A, Saguna S, Mitra K, Jayaraman PP, Rabhi F, Ranjan R. Remote healthcare cyber-physical system:quality of service (QoS) challenges and opportunities. IET Cyber-Physical Systems: Theory & Applications 2016, 1(1), 40-48.
- Shah T, Rabhi F, Ray T. Investigating an ontology-based approach for Big Data analysis of inter-dependent medical and oral health conditions. Cluster Computing 2015, 18(1), 351-367.
- Shah T, Rabhi F, Ray P, Taylor K. A guiding framework for ontology reuse in the biomedical domain. In: 47th Hawaii International Conference on System Sciences. 2014, Waikoloa, HI, USA: IEEE.
- Shah T, Rabhi F, Ray P, Taylor K. Enhancing automated decision support across Medical and Oral Health domains with semantic web technologies. In: 24th Australasian Conference on Information Systems (ACIS). 2013, Melbourne, Australia: RMIT University.
- Shah T, Rabhi F, Ray P. OSHCO: A cross-domain ontology for semantic interoperability across medical and oral health. In: 15th International Conference on e-Health Networking, Applications & Services (Healthcom). 2013, Lisbon, Portugal: IEEE.
- Han W, Deng Z, Chu J, Zhu J, Gao P, Shah T. A parallel online trajectory compression approach for supporting big data workflow. Computing 2018, 100(1), 3-20.
- Ke H, Chen D, Li X, Tang Y, Shah T, Ranjan R. Towards Brain Big Data Classification: Epileptic EEG Identification with a Lightweight VGGNet on Global MIC. IEEE Access 2018, Epub ahead of print.