IOT AND CLOUD BASED MEDICAL DISEASE DIAGNOSIS AND CLASSIFICATION MODEL USING OPTIMAL KERNEL EXTREME LEARNING MACHINE.
Due to the development of Internet of Things (IoT) and related devices in the healthcare sector, diverse set of medical applications and services becomes feasible. The massive quantity of healthcare data produced by IoT devices requires cloud computing platform for handling it. This paper presents a...
| Publicado en: | Turkish Journal of Physiotherapy Rehabilitation Vol. 32; no. 2; pp. 3088 - 3100 |
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| Autores principales: | , , |
| Formato: | equations & formulas tables/charts Journal Article |
| Publicado: |
Turkish Journal of Physiotherapy & Rehabilitation
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151006332&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 151006332 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13008757 YU1 jtl: Turkish Journal of Physiotherapy Rehabilitation issn: 13008757 maglogo: N pubinfo: dt: 2021 vid: 32 iid: 2 pid: 20392 pub: Turkish Journal of Physiotherapy & Rehabilitation place: Kizilay/ Ankara, <Blank> artinfo: ui: 151006332 151006332 151006332 151006332 ppf: 3088 ppct: 12 formats: fmt: @attributes: type: P tig: atl: IOT AND CLOUD BASED MEDICAL DISEASE DIAGNOSIS AND CLASSIFICATION MODEL USING OPTIMAL KERNEL EXTREME LEARNING MACHINE. aug: au: RAGUPATHI, T. GOVINDARAJAN, M. DEVI, T. PRIYA RADHIKA affil: Research Scholar, Department of Computer Science and Engineering Annamalai University sug: subj: Disease Diagnosis Cloud Computing Learning Methods Internet of Things Prediction Models Teaching Methods Algorithms Extreme Learning Machines Computer Simulation Performance Measurement Systems Benchmarking ab: Due to the development of Internet of Things (IoT) and related devices in the healthcare sector, diverse set of medical applications and services becomes feasible. The massive quantity of healthcare data produced by IoT devices requires cloud computing platform for handling it. This paper presents a new IoT and Cloud Enabled Disease Diagnosis and Prediction Model using Teaching and Learning based Optimization (TLBO) Algorithm with Kernel Extreme Learning Machine (KELM), named TLBO-KELM model. The proposed model initially performs data collection, where the acquisition of healthcare data takes place using three sources such as IoT devices, benchmark data repositories, and medical records. Then, the TLBO-KELM model gets executed to diagnose and predict the existence of diseases using the patient data. Besides, the application of TLBO algorithm in KELM helps to effectively tune the parameters for achieving better classification performance. The performance of the TLBO-KELM model has been tested against benchmark pimaindian diabetes dataset. The simulation outcome ensured that the TLBO-KELM model has outperformed the earlier models in a significant manner. pubtype: Academic Journal doctype: equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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