DLRS:Deep Learning-Based Recommender System for Smart Healthcare Ecosystem

Aujla, G.S. and Jindal, A. and Chaudhary, R. and Kumar, N. and Vashist, S. and Sharma, N. and Obaidat, M.S. (2019) DLRS:Deep Learning-Based Recommender System for Smart Healthcare Ecosystem. In: 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings. IEEE. ISBN 9781538680896

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Abstract

Nowadays, the conventional healthcare domain has witnessed a paradigm shift towards patient-driven healthcare 4.0 ecosystem. In this direction, healthcare recommender systems provide ubiquitous healthcare services to the end users even on the move. However, there are various challenges for the design of patient driven healthcare recommender systems. Some of the major challenges are: a) handling huge amount of data generated by smart devices and sensors, b) dynamic network management for real-time data transmission, and c) lack of knowledge gathering and aggregation methods. For these reasons, in this paper; DLRS: A Deep Learning based Recommender System using software defined networking (SDN) is designed for smart healthcare ecosystem. DLSR works in the following phases: a) a tensor-based dimensionality reduction algorithm is proposed for removing unwanted dimensions in the acquired data, b) a decision tree-based classification scheme is presented for categorization of the patient queries on the basis of different diseases, and c) a convolutional neural network based system is designed for providing recommendations about the patient health. On evaluation, the results obtained prove the superiority of the proposed scheme in contrast to existing competing schemes.

Item Type:
Contribution in Book/Report/Proceedings
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ID Code:
136299
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Deposited On:
13 Sep 2019 09:00
Refereed?:
Yes
Published?:
Published
Last Modified:
22 Oct 2020 07:44