[
  {
    "id": "10.1201/9781003424987-3",
    "type": "chapter",
    "title": "Smart Health: Advancements in Machine Learning and the Internet of Things Solutions",
    "author": [
      {
        "family": "Vajjhala",
        "given": "Narasimha Rao"
      },
      {
        "family": "Eappen",
        "given": "Philip"
      }
    ],
    "editor": [
      {
        "literal": "Pijush Samui"
      },
      {
        "literal": "Sanjiban Sekhar Roy"
      },
      {
        "literal": "Wengang Zhang"
      },
      {
        "literal": "Y-h. Taguchi"
      }
    ],
    "container-title": "Machine Learning and IoT Applications for Health Informatics",
    "issued": {
      "date-parts": [
        [
          2024,
          10,
          2
        ]
      ]
    },
    "page": "31-51",
    "publisher": "CRC Press",
    "ISBN": "9781003424987",
    "DOI": "10.1201/9781003424987-3",
    "URL": "https://www.narasimharao.net/research/smart-health-machine-learning-internet-of-things/",
    "abstract": "This chapter examines the transformative intersection of healthcare analytics, Machine Learning (ML), and the Internet of Things (IoT), exploring how these state-of-the-art technologies reshape healthcare delivery. This chapter focuses on the benefits brought about by the synergy of ML and IoT in the healthcare sector, such as enhanced patient care, early disease detection, operational efficiency, and personalized treatment plans. We explore the problems and challenges of integrating ML and IoT with healthcare analytics and recommend solutions in this chapter. The chapter also addresses ethical, practical, and security considerations, emphasizing the importance of data privacy, model interpretability, bias mitigation, and secure connectivity in deploying healthcare technology. Furthermore, this chapter also presents the ongoing technological advancements and their potential to augment healthcare analytics further, emphasizing the need for patient-centric approaches and addressing global health disparities. This chapter explores healthcare analytics’ current landscape and prospects, considering the integration of ML and IoT solutions.",
    "keyword": "smart health, healthcare analytics, machine learning in healthcare, Internet of Things, IoT in healthcare, early disease detection, personalised treatment, data privacy, model interpretability, bias mitigation, secure connectivity, global health disparities, healthcare informatics",
    "language": "en"
  }
]