Pharmacovigilance predictive analysis using NLP-based cloud

被引:3
|
作者
Madhan, E. S. [1 ]
机构
[1] Anna Univ, Informat & Commun Engn, Madras, Tamil Nadu, India
关键词
cloud computing; pharmacovigilance; natural language processing; big data; IOT; ADR; adverse drug reaction; healthcare;
D O I
10.1504/IJBET.2018.10011136
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Nowadays, healthcare on Big data are a major research area in Computer Science field. This paper presents a mysterious analysis of pharmacovigilance from reviewers using NLP cloud environment. The historical and comparative methods upon doctors' prescription data and analysis are performed in the NLP (Natural Language Processing) cloud. For improving analysis of pharmacovigilance in medical research our system of approach not only explains the healthcare monitoring system but also scalable psychoanalysis of medical data. The system of approach explored by the variation of offline and online feedbacks of patients and it reveals through sentimental analysis in the NLP cloud system. Pharmacovigilance in NLP cloud analysis process identified the emotional analysis of the patient medicine intake data. The existing conventional methods of pharmacovigilance are taken upon clinical trials and small groups of tests data. The comparison result helps to find quicker analysis of medicine intake of the patients and protect from adverse drug event. Our approach will gain with the effort by the pharmacovigilance in cloud for patients. This innovation furnishes patients and specialists with openness to data that can enhance healthcare by investigating the primary as well as secondary data. A novelty approach which will make better service for tablets and pharma products in the medical field and as well as avoids overdosage and adverse effect event.
引用
收藏
页码:316 / 324
页数:9
相关论文
共 50 条
  • [1] An NLP-based citation reason analysis using CCRO
    Ihsan, Imran
    Qadir, M. Abdul
    [J]. SCIENTOMETRICS, 2021, 126 (06) : 4769 - 4791
  • [2] An NLP-based citation reason analysis using CCRO
    Imran Ihsan
    M. Abdul Qadir
    [J]. Scientometrics, 2021, 126 : 4769 - 4791
  • [3] An NLP-based Tool for Software Artifacts Analysis
    Di Sorbo, Andrea
    Visaggio, Corrado A.
    Di Penta, Massimiliano
    Canfora, Gerardo
    Panichella, Sebastiano
    [J]. 2021 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE AND EVOLUTION (ICSME 2021), 2021, : 569 - 573
  • [4] Comparative Analysis of NLP-Based Models for Company Classification
    Rizinski, Maryan
    Jankov, Andrej
    Sankaradas, Vignesh
    Pinsky, Eugene
    Mishkovski, Igor
    Trajanov, Dimitar
    [J]. INFORMATION, 2024, 15 (02)
  • [5] Semantic Search and NLP-Based Diagnostics
    Kats, Yefim
    [J]. 2014 IEEE 27TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS (CBMS), 2014, : 277 - 280
  • [6] Practical NLP-based text indexing
    Vilares, J
    Barcala, FM
    Alonso, MA
    Graña, J
    Vilares, M
    [J]. ADVANCES IN ARTIFICIAL INTELLIGENCE - IBERAMIA 2002, PROCEEDINGS, 2002, 2527 : 635 - 644
  • [7] Query reformulation and refinement using NLP-based sentence clustering
    Roulland, Frederic
    Kaplan, Aaron
    Castellani, Stefania
    Roux, Claude
    Grasso, Antonietta
    Pettersson, Karin
    O'Neill, Jacki
    [J]. ADVANCES IN INFORMATION RETRIEVAL, 2007, 4425 : 210 - +
  • [8] NLP-based music processing for composer classification
    Deepaisarn, Somrudee
    Chokphantavee, Sirawit
    Chokphantavee, Sorawit
    Prathipasen, Phuriphan
    Buaruk, Suphachok
    Sornlertlamvanich, Virach
    [J]. SCIENTIFIC REPORTS, 2023, 13 (01)
  • [9] NLP-based curation of bacterial regulatory networks
    Rodriguez-Penagos, Carlos
    Salgado, Heladia
    Martinez-Flores, Irma
    Collado-Vides, Julio
    [J]. COMPUTATIONAL LINGUISTICS AND INTELLIGENT TEXT PROCESSING, 2007, 4394 : 575 - +
  • [10] NLP-based Sentiment Analysis for Twitter's Opinion Mining and Visualization
    Al-Ghalibi, Maha
    Al-Azzawi, Adil
    Lawonn, Kai
    [J]. ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2018), 2019, 11041