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This paper aims to investigate all aspects of Internet of Things (IoT) based smart healthcare recent research trend with machine learning support. Various challenges and proposed solutions available in recent papers have also been analyzed. Recent relevant research papers published between 2010 and 2023 have been focused upon. Health monitoring, disease prediction and diagnosis, outbreak prediction, personalized treatment, energy efficient system, secured healthcare frameworks etc. are the different research wings in healthcare domain have been explored in detail. Also some of the research papers in similar domain have been compared with our paper based on their key focus areas. Total 880 papers are selected from popular scientific databases like IEEE Xplore, Elsevier, Springer Link, ACM and BMC for detailed study. Out of 880 papers, 97 papers are presented in detail in different research categories to ignite interested researchers’ mind towards appropriate research direction. A dataset is taken from ADNI and different deep learning algorithms are applied and our proposed model gives accuracy 97.25% for AD, 98.33% for MCI and 97.54% for NC.

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Extensive Investigation on Smart Healthcare Towards Disease Classification Using Deep Learning

  • 会议论文

  • 发表日期：

    2025年

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  • Mayurakshi Jana,
  • Suparna Biswas

摘要

This paper aims to investigate all aspects of Internet of Things (IoT) based smart healthcare recent research trend with machine learning support. Various challenges and proposed solutions available in recent papers have also been analyzed. Recent relevant research papers published between 2010 and 2023 have been focused upon. Health monitoring, disease prediction and diagnosis, outbreak prediction, personalized treatment, energy efficient system, secured healthcare frameworks etc. are the different research wings in healthcare domain have been explored in detail. Also some of the research papers in similar domain have been compared with our paper based on their key focus areas. Total 880 papers are selected from popular scientific databases like IEEE Xplore, Elsevier, Springer Link, ACM and BMC for detailed study. Out of 880 papers, 97 papers are presented in detail in different research categories to ignite interested researchers’ mind towards appropriate research direction. A dataset is taken from ADNI and different deep learning algorithms are applied and our proposed model gives accuracy 97.25% for AD, 98.33% for MCI and 97.54% for NC.