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REVIEW article

Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 7 - 2024 | doi: 10.3389/frai.2024.1442254

Assuring assistance to healthcare and medicine: Internet of Things (IoT), Artificial intelligence (AI), and Artificial Intelligence of Things (AIOT)

Provisionally accepted
Poshan Belbase Poshan Belbase 1Rajan Bhusal Rajan Bhusal 2*Sapana Sharma Ghimire Sapana Sharma Ghimire 3shreesti Sharma shreesti Sharma 4Bibek Banskota Bibek Banskota 2
  • 1 The Catholic University of America, Washington, D.C., District of Columbia, United States
  • 2 Hospital and Rehabilitation Centre for Disabled Children, Banepa, Nepal
  • 3 Tribhuvan University, Kirtipur, Nepal
  • 4 Marie stopes Nepal, Kathmandu, Nepal

The final, formatted version of the article will be published soon.

    Introduction: The convergence of healthcare with the Internet of Things (IoT) and Artificial Intelligence (AI) is reshaping medical practice with promising enhanced data-driven insights, automated decision-making, and remote patient monitoring. It has the transformative potential of these technologies to revolutionize diagnosis, treatment, and patient care. Purpose: This study aims to explore the integration of IoT and AI in healthcare, outlining their applications, benefits, challenges, and potential risks. By synthesizing existing literature, this study aims to provide insights into the current landscape of AI, IoT, and AIOT in healthcare, identify areas for future research and development, and establish a framework for the effective use of AI in health. Method: A comprehensive literature review included indexed databases such as PubMed/Medline, Scopus, and Google Scholar. Key search terms related to IoT, AI, healthcare, and medicine were employed to identify relevant studies. Papers were screened based on their relevance to the specified themes, and eventually, a selected number of papers were methodically chosen for this review. Results: The integration of IoT and AI in healthcare offers significant advancements, including remote patient monitoring, personalized medicine, and operational efficiency. Wearable sensors, cloud-based data storage, and AI-driven algorithms enable real-time data collection, disease diagnosis, and treatment planning. However, challenges such as data privacy, algorithmic bias, and regulatory compliance must be addressed to ensure responsible deployment of these technologies. Conclusion: Integrating IoT and AI in healthcare holds immense promise for improving patient outcomes and optimizing healthcare delivery. Despite challenges such as data privacy concerns and algorithmic biases, the transformative potential of these technologies cannot be overstated. Clear governance frameworks, transparent AI decision-making processes, and ethical considerations are essential to mitigate risks and harness the full benefits of IoT and AI in healthcare.

    Keywords: machine learning, Deep learning and NLP, LLMS, AI, IOT in medicine, AIoT

    Received: 01 Jun 2024; Accepted: 28 Nov 2024.

    Copyright: © 2024 Belbase, Bhusal, Ghimire, Sharma and Banskota. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Rajan Bhusal, Hospital and Rehabilitation Centre for Disabled Children, Banepa, Nepal

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.