Abstract
With the development of technologies such as Internet of Things, Cloud Computing, Big Data and Machine Learning, created business models and information systems based on these business models have the need for restructuring. Medical Laboratories are environments where technical devices are located. New generation devices also have the IoT infrastructure. Thus, these devices support the transfer of device data to the relevant health information system through cloud computing. Monitoring the operating conditions, estimated maintenance periods and calibration settings for the specified devices on a common platform will increase the quality and reliability of the measurement results to be determined through the device. In this paper, a new generation LIS architecture, named LabHub, is proposed. With the platform which will be developed on LabHub architecture, traceability of the devices in all public and private sector, domestic and international medical laboratories will be provided with a cloud application that serves as a software principle. The data collected through the device will be stored in the cloud database with a scalable big data model in the cloud application by protecting the privacy of personal data and even free from personal data. Any violations that may occur in this data will be determined in a special way to the device and the operation performed on the device. Methods based on machine learning algorithms will be used to identify contradictory situations. Thus, the infrastructure for both the measurement of the desired quality of the devices and the reliable recording of the measurement results will be developed.
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Idemen, B.T., Sezer, E., Unalir, M.O. (2021). LabHub: A New Generation Architecture Proposal for Intelligent Healthcare Medical Laboratories. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I., Cebi, S., Tolga, A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. https://doi.org/10.1007/978-3-030-51156-2_150
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DOI: https://doi.org/10.1007/978-3-030-51156-2_150
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