首页|Studies from University of Manchester in the Area of Artificial Intelligence Des cribed (Artificial Intelligence In Nursing and Midwifery: a Systematic Review)
Studies from University of Manchester in the Area of Artificial Intelligence Des cribed (Artificial Intelligence In Nursing and Midwifery: a Systematic Review)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ar tificial Intelligence. According to news reporting from Manchester, United Kingd om, by NewsRx journalists, research stated, “Artificial Intelligence (AI) techni ques are being applied in nursing and midwifery to improve decision-making, pati ent care and service delivery. However, an understanding of the real-world appli cations of AI across all domains of both professions is limited.” The news correspondents obtained a quote from the research from the University o f Manchester, “To synthesise literature on AI in nursing and midwifery. CINAHL, Embase, PubMed and Scopus were searched using relevant terms. Titles, abstracts and full texts were screened against eligibility criteria. Data were extracted, analysed, and findings were presented in a descriptive summary. The PRISMA check list guided the review conduct and reporting. One hundred and forty articles wer e included. Nurses’ and midwives’ involvement in AI varied, with some taking an active role in testing, using or evaluating AI-based technologies; however, many studies did not include either profession. AI was mainly applied in clinical pr actice to direct patient care (n = 115, 82.14%), with fewer studies focusing on administration and management (n = 21, 15.00%), or edu cation (n = 4, 2.85%). Benefits reported were primarily potential a s most studies trained and tested AI algorithms. Only a handful (n = 8, 7.14% ) reported actual benefits when AI techniques were applied in real-world setting s. Risks and limitations included poor quality datasets that could introduce bia s, the need for clinical interpretation of AI-based results, privacy and trust i ssues, and inadequate AI expertise among the professions. Digital health dataset s should be put in place to support the testing, use, and evaluation of AI in nu rsing and midwifery. Curricula need to be developed to educate the professions a bout AI, so they can lead and participate in these digital initiatives in health care.”
Manchester, United Kingdom, Europe, Arti ficial Intelligence, Emerging Technologies, Health and Medicine, Machine Learnin g, Midwifery, Technology, University of Manchester
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