IDEAS home Printed from https://ideas.repec.org/a/abq/ijist1/v5y2023i2p160-178.html
   My bibliography  Save this article

Applications of AI in Health Services

Author

Listed:
  • Qura tul Ain

    (Lahore College for Women University Lahore)

Abstract

The effects of artificial intelligence (AI)-based technologies on the healthcare sector are explored in this study.This research examined numerous practical uses of AI in healthcare, in addition to a comprehensive literature evaluation. Based on these findings, it appears that large hospitals are currently utilizing AI-enabled technologies to assist with patient diagnostic and treatment activities across a wide variety of ailments. Additionally, AI technologies are affectingthe effectiveness of nursing and hospital management. Although AI is generally welcomed by the healthcare industry, its implementations present both utopian (new possibilities) and dystopian (overcoming obstacles) scenarios. To present a well-rounded picture of the usefulness of AI applications in healthcare, we address the specifics of these potential obstacles. The rapid development of AI and associated technologies will aid in the improvement of operational efficiency and the creation of new value for patients. However, to gain the benefits of technology like AI, comprehensive service transformation and operations planning are essential.

Suggested Citation

  • Qura tul Ain, 2023. "Applications of AI in Health Services," International Journal of Innovations in Science & Technology, 50sea, vol. 5(2), pages 160-178, June.
    • Handle: RePEc:abq:ijist1:v:5:y:2023:i:2:p:160-178
    as

    Download full text from publisher

    File URL: https://journal.50sea.com/index.php/IJIST/article/view/507/1028
    Download Restriction: no
    File URL: https://journal.50sea.com/index.php/IJIST/article/view/507
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lisa M. McShane & Margaret M. Cavenagh & Tracy G. Lively & David A. Eberhard & William L. Bigbee & P. Mickey Williams & Jill P. Mesirov & Mei-Yin C. Polley & Kelly Y. Kim & James V. Tricoli & Jeremy M, 2013. "Criteria for the use of omics-based predictors in clinical trials," Nature, Nature, vol. 502(7471), pages 317-320, October.
    2. Su-In Lee & Safiye Celik & Benjamin A. Logsdon & Scott M. Lundberg & Timothy J. Martins & Vivian G. Oehler & Elihu H. Estey & Chris P. Miller & Sylvia Chien & Jin Dai & Akanksha Saxena & C. Anthony Bl, 2018. "A machine learning approach to integrate big data for precision medicine in acute myeloid leukemia," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zamir G Merali & Christopher D Witiw & Jetan H Badhiwala & Jefferson R Wilson & Michael G Fehlings, 2019. "Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-12, April.
    2. Markus Eyting, 2020. "A Random Forest a Day Keeps the Doctor Away," Working Papers 2026, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    3. David Wang & Mathieu Quesnel-Vallieres & San Jewell & Moein Elzubeir & Kristen Lynch & Andrei Thomas-Tikhonenko & Yoseph Barash, 2023. "A Bayesian model for unsupervised detection of RNA splicing based subtypes in cancers," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    4. Michael Brimacombe, 2025. "Simpson’s Paradox: Aggregation Effects in Statistical and Machine Learning Models," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 14(2), pages 1-5, July.
    5. Asma Chaibi & Imed Zaiem, 2022. "Doctor Resistance of Artificial Intelligence in Healthcare," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global Scientific Publishing, vol. 17(1), pages 1-13, January.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:abq:ijist1:v:5:y:2023:i:2:p:160-178. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Iqra Nazeer (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.