sc 22(3): e2

Research Article

Current practices and Limitations in E Health Informatics

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  • @ARTICLE{10.4108/eetsc.v6i3.2271,
        author={Umamaheshwari K. and Manju Rathinam and Vivekitha V. and Dinesh T. N.},
        title={Current practices and Limitations in E Health Informatics},
        journal={EAI Endorsed Transactions on Smart Cities},
        volume={6},
        number={3},
        publisher={EAI},
        journal_a={SC},
        year={2022},
        month={9},
        keywords={E-health, Cognitive Disorder, Therapy, Healthcare},
        doi={10.4108/eetsc.v6i3.2271}
    }
    
  • Umamaheshwari K.
    Manju Rathinam
    Vivekitha V.
    Dinesh T. N.
    Year: 2022
    Current practices and Limitations in E Health Informatics
    SC
    EAI
    DOI: 10.4108/eetsc.v6i3.2271
Umamaheshwari K.1, Manju Rathinam2,*, Vivekitha V.2, Dinesh T. N.2
  • 1: Kebri Dehar University, Kebri Dehar, Ethiopia
  • 2: Institute of Technology, Coimbatore, India
*Contact email: manjufeb62@gmail.com

Abstract

E-health is a field which as seen tremendous growth in the recent times especially after the covid-19 outbreak. E-health offers the potential to provide patients with high-quality care at a reasonable cost in the ease of their own homes. E-health has a wide range of application that includes rehabilitation, cognitive disorder, behavioural therapy, defence application and many more. E-health as a technology is changing tremendously and always been evolving to meet the demands of the current practices. But still, it has certain challenges in implementing such as ethical issues, patient contest etc. Artificial intelligence framework capable of using non-consultancy, reinforcement learning, and all three. Controlling the processes within the m-Health application, choosing the best processes that can be used to alter the user's existing conditions, or selecting the best diagnosis-solution from an array of choices are all supported by intelligent optimization algorithms that can offer faster feedback.