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Big Data in Medical Image Processing
Published in R. Suganya, S. Rajaram, A. Sheik Abdullah, Big Data in Medical Image Processing, 2018
R. Suganya, S. Rajaram, A. Sheik Abdullah
A tactical plan for big data in medical imaging, it is to dynamically integrate medical images, in vitro diagnostic information, genetic information, electronic health records and clinical notes into a patient’s profile. This provides the ability for personalized decision support by the analysis of data from large numbers of patients with similar conditions. Big data has potential to be a valuable tool, but implementation can pose a challenge in building a medical report with context-specific and target group-specific information that requires access and analysis of big data. The report can be created with the help of semantic technology, an umbrella term used to describe natural language processing, data mining, artificial intelligence, tagging and searching by concept instead of by key word. Radiology can add value to the era of big data by supporting implementation of structured reports.
Ontology-Based Information Retrieval and Matching in IoT Applications
Published in Brojo Kishore Mishra, Raghvendra Kumar, Natural Language Processing in Artificial Intelligence, 2020
M. Lawanya Shri, E. Ganga Devi, Balamurugan Balusamy, Jyotir Moy Chatterjee
Ontologies are currently used in the IoT application for knowledge representation and for structuring the sensed information of a specific domain. The main objective of this chapter is for designing an information processing model for IoT applications based on the semantic web and for integrating ontologies for enriching the information gathered from the sensors. Semantic technology plays a vital role in combining the entities, gathering, and monitoring the data.
Data Science with Semantic Technologies: Application to Information Systems Development
Published in Journal of Computer Information Systems, 2023
The ultimate goal of semantic technology is to help machines understand data by enabling an explicit representation of the semantics (meaning) of data. This means that among such technologies those which allow defining the meaning of entities residing in a domain (e.g. ontologies, by describing concepts, relationships between things, and categories of things), representing and storing the entities according to such definition, and capturing meaningful information related to the entities once they are stored. These embedded semantics with the data offer significant advantages such as reasoning over data and dealing with heterogeneous data source.51 By approaching the automatic understanding of meanings, semantic technology overcomes the limits of other technologies.
Framework and modelling of inclusive manufacturing system
Published in International Journal of Computer Integrated Manufacturing, 2019
Sube Singh, Biswajit Mahanty, Manoj Kumar Tiwari
This work only proposes the concept of IMS with its elements, but implementation of IMS can be realised by the government or any LEs with the support of several multination companies (Google, Facebook, Amazon, IBM and many more). The supporting companies provide cloud services (as a platform, software, application and infrastructure), tools and types of machinery on requirement basis by facilitating Tool Room Centres at geographically distributed locations. The framework helps in realising the practicability of IMS, with significant arrangement of information related to consumers, enterprises, manufacturer and service providers and track the product from order to final delivery. Figure 8 denotes information required in developing the IMS such as customer details, product details, AI techniques, logistics services, manufacturing units, software etc. All the participants get registered in developed platform of IMS by providing the vital information as mentioned in Figures 8. Semantic technology assists the system in accessing the linked data from various ontological structure related to enterprise, product, operation and life cycle management. The policies and standards layer apply to all stages of participants, for example manufacturer needs to follow certain quality and environmental standards along with obeying labour laws. Similarly, the communication layer ensures the support of better communication among all the entities by adopting emerging ICT. The logistics information layer helps in increasing the data sharing among the partners of logistics systems at all levels from manufacturer to final delivery with real-time traceability with IoT devices implementation. The companies facilitate enterprise software and business-oriented tools as mentioned in application and global service layer for supporting the stakeholders. Users get access to the system for making an order and giving the feedback with help of a portal by using GUI.