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A Review on Innovation in Healthcare Sector (Telehealth) through Artificial Intelligence

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  • Ayesha Amjad

    (Faculty of Organization and Management, Silesian University of Technology, 44-100 Gliwice, Poland
    CEMMPRE, Department of Mechanical Engineering, University of Coimbra, Polo II, 3030-788 Coimbra, Portugal)

  • Piotr Kordel

    (Faculty of Organization and Management, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Gabriela Fernandes

    (CEMMPRE, Department of Mechanical Engineering, University of Coimbra, Polo II, 3030-788 Coimbra, Portugal)

Abstract

Artificial intelligence (AI) has entered the mainstream as computing power has improved. The healthcare industry is undergoing dramatic transformations at present. One of the most recent industries to heavily use AI is telehealth, which is used for anything from issuing electronic healthcare cards to providing individual counselling. Artificial intelligence (AI) is influencing telehealth in the United States in a major way. Using AI in telehealth to allow clinicians to make real-time, data-driven rich choices is critical to offering a better patient experience and improved health outcomes as practitioners strive toward expanding virtual care options along the care continuum. Research in the medical industry has started to use AI’s strengths in data processing and analysis in telehealth, reflecting the widespread adoption of AI in other sectors. Because of the difficulties inherent in telemedicine’s deployment, there is an urgent need to broaden its capabilities and enhance its processes so that they may be tailored to address particular issues. This article is aimed to study different areas of telemedicine and analyze the effect of AI in the field of health and medicine. The literature surveyed in this study demonstrates the infinite growth potential afforded by the combination of AI and telemedicine. There are four main directions that the expanding use of this technology is heading: patient monitoring, healthcare IT, intelligent aid in diagnosis, and information analysis with other specialists.

Suggested Citation

  • Ayesha Amjad & Piotr Kordel & Gabriela Fernandes, 2023. "A Review on Innovation in Healthcare Sector (Telehealth) through Artificial Intelligence," Sustainability, MDPI, vol. 15(8), pages 1-24, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6655-:d:1123642
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    References listed on IDEAS

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    1. Yudong Zhang & Saeed Balochian & Praveen Agarwal & Vishal Bhatnagar & Orwa Jaber Housheya, 2014. "Artificial Intelligence and Its Applications," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, April.
    2. Abdel-Basset, Mohamed & Chang, Victor & Nabeeh, Nada A., 2021. "An intelligent framework using disruptive technologies for COVID-19 analysis," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. Zirar, Araz & Ali, Syed Imran & Islam, Nazrul, 2023. "Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda," Technovation, Elsevier, vol. 124(C).
    4. Wang, Yichuan & Hajli, Nick, 2017. "Exploring the path to big data analytics success in healthcare," Journal of Business Research, Elsevier, vol. 70(C), pages 287-299.
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    Cited by:

    1. Xian Gao & Peixiong He & Yi Zhou & Xiao Qin, 2024. "Artificial Intelligence Applications in Smart Healthcare: A Survey," Future Internet, MDPI, vol. 16(9), pages 1-32, August.

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