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O’Connor, S., Yan, Y., Thilo, F.J.S., Felzmann, H., Dowding, D. and Lee, J.J. (2023) Artificial Intelligence in Nursing and Midwifery: A Systematic Review. Journal of Clinical Nursing, 32, 2951-2968.
https://doi.org/10.1111/jocn.16478

has been cited by the following article:

• TITLE: The Role of Artificial Intelligence in the Medical Field

  AUTHORS: Shridula Kapa

  KEYWORDS: Artificial Intelligence, Medical Field, Role of A. I. in Healthcare, Advantages of A. I., Disadvantages of A. I. in Medical Field

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.11, November 8, 2023

  ABSTRACT: The Artificial Intelligence in the medical field has revolutionized the industry. Recently, A. I. has interested medical practitioners in applying innovation to healthcare systems. A. I. has еmеrgеd as a transformative forcе, revolutionizing the industry by leveraging advanced algorithms and computing powеr to еnhancе various aspects of hеalthcarе dеlivеry. The background highlights that artificial intelligence as innovation promises to transform how medical staffs manage patients and treat and diagnose patients. This comprehensive literature review to identify the relevant sources of information on A. I implementation in healthcare, focusing on the advantages and disadvantages. The obtained results from the materials provided valuable insights into the various means A. I. is used in the medical industry and its effects on patient care and recovery. The findings indicated that; A. I. streamlines Tedious Tasks since it is accurate and gives speedy services enabling early detection of illnesses and leading to positive patient outcomes. A. I. provides Real-Time Data which is essential in addressing patients’ conditions with clear objectives; the use of A. I. improves helps to reduce Burnout in medical practitioners. The use of A. I. helps provide Precision Medicine since it can obtain and analyze large amounts of information. The future directions encompass the implementation of the legal framework, enhancing transparency and accountability, and addressing challenges related to data standardization.