The essential mission of Johns Hopkins College in Baltimore incorporates a guarantee to propelling information and furnishing understudies with elite training. Man-made intelligence innovation can assume a part in this mission by supporting and upgrading the learning of nursing understudies at the college (Amann et al., 2020).
One way that artificial intelligence innovation can uphold the essential mission of Johns Hopkins College is by giving customized and versatile growth opportunities for nursing understudies. Man-made intelligence-based learning devices can investigate understudy information and adjust to the requirements and capacities of every individual understudy, giving a more custom-made growth opportunity. This can assist understudies with learning all the more really and effectively, possibly prompting further developed test scores and maintenance of data.
Another way that simulated intelligence innovation can uphold the essential mission of Johns Hopkins College is by giving understudies chances to rehearse and foster their clinical abilities in a protected, controlled climate. Artificial intelligence-based learning apparatuses can mimic clinical situations and permit understudies to rehearse their abilities, working on their readiness for genuine clinical circumstances. Generally speaking, the utilization of man-made intelligence innovation in the training of nursing at Johns Hopkins College can assist with propelling information and furnish understudies with a top notch schooling, lining up with the college’s essential mission (Gardner et al., 2018).
The utilization of innovation has additionally given ideal outcomes in each field of life. Man-made reasoning is pretty much as old as Data Innovation (IT). Man-made intelligence has created learning strategies and showing modules and unbelievably turned the method of knowledge for understudies. Programmed handling and examination of information will assist nursing understudies with getting better clinical practices and guarantee patient consideration and security.
Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: A multidisciplinary perspective. BMC Medical Informatics and Decision Making, 20(1).
https://doi.org/10.1186/s12911-020-01332-6
Buchanan, C., Howitt, M. L., Wilson, R., Booth, R. G., Risling, T., & Bamford, M. (2021). Predicted Influences of Artificial Intelligence on Nursing Education: Scoping Review. JMIR Nursing, 4(1), e23933.
https://doi.org/10.2196/23933
Gardner, R. L., Cooper, E., Haskell, J., Harris, D. A., Poplau, S., Kroth, P. J., & Linzer, M. (2018). Physician stress and burnout: the impact of health information technology. Journal of the American Medical Informatics Association, 26(2), 106–114. https://doi.org/10.1093/jamia/ocy145
Pottle, J. (2019). Virtual reality and the transformation of medical education. Future Healthcare Journal, 6(3), 181–185.
https://doi.org/10.7861/fhj.2019-0036
Randhawa, G. K., & Jackson, M. (2019). The role of artificial intelligence in learning and professional development for healthcare professionals. Healthcare Management Forum, 33(1), 19–24.
https://doi.org/10.1177/0840470419869032
Robert, N. (2019). How artificial intelligence is changing nursing. Nursing Management (Springhouse), 50(9), 30–39.
https://doi.org/10.1097/01.numa.0000578988.56622.21
Shorey, S., Ang, E., Yap, J., Ng, E. D., Lau, S. T., & Chui, C. K. (2019). A Virtual Counseling Application Using Artificial Intelligence for Communication Skills Training in Nursing Education: Development Study. Journal of Medical Internet Research, 21(10), e14658. https://doi.org/10.2196/14658
Struggling with online classes or exams? Get expert help to ace your coursework, assignments, and tests stress-free!