AI-Empowered Healthcare: Redefining Human Skills for Smarter, Patient-Centric Systems
DOI:
https://doi.org/10.54489/yymr7a11Keywords:
Artificial Intelligence (AI), Smart Healthcare, Precision Medicine’ Clinical Decision Support, Human Skills Transformation, Digital HealthAbstract
Abstract
The technological advancements are invariably re-shaping the economy, and the emergence of Artificial Intelligence as the panacea is in the health sector. This thesis contemplates AI's fundamental function in avoiding healthcare system revolution including such processes as diagnosis, treatment, personalized medicine, and administrative functions among many others.
AI algorithms, which include machine learning and deep learning techniques, have been shown impressive results in diagnosing and predicting the onset of diseases. Furthermore, the AI-based decision support systems can play the role of supporting clinical decision making since real-time insights as well as big data are easy to use by these systems, ultimately leading to improved treatment strategy with quality patient outcomes.
This coupled with the development of an AI in precision medicine has also led to the development of personalized interventions to fit the genetic, environmental, and lifestyle factors of an individual. The establishment of such a system has started a personalized care era. Moreover, AI-equipped tools help in the interpretation of medical images and genetic data, which in turn improves the process of locating biomarkers or finding therapeutic targets for complex diseases.
AI-based systems have facilitated not only medical procedures but also, they have improved the efficiency of administrative stuffs such as appointment making, billing and electronic health record maintenance. This always results in better operational efficiencies and cost saving in healthcare institutions as a result. Furthermore, AI-enabled chatbots and virtual assistance have been an instrumental factor in boosting patient engagement and granting patient access to healthcare services, particularly in distal or disenfranchised areas.
Nevertheless, AI finds its usage in healthcare has its flip side the challenges and ethical concerns though. It has addressed topics including data privacy, algorithm biases, and also raised attention on the need for regulatory body. It includes the effects of AI on healthcare workforce as well highlighting the need for upskilling and reskilling of workers required for complete utilization of AI potential.
References
Secinaro, S., Calandra, D., Secinaro, A., Muthurangu, V., & Biancone, P. (2021). The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making, 21, 1-23.
Klumpp, M., Hintze, M., Immonen, M., Ródenas-Rigla, F., Pilati, F., Aparicio-Martínez, F., ... & Delgado-Gonzalo, R. (2021, July). Artificial intelligence for hospital health care: Application cases and answers to challenges in European hospitals. In Healthcare (Vol. 9, No. 8, p. 961). MDPI.
Strohm, L., Hehakaya, C., Ranschaert, E. R., Boon, W. P., & Moors, E. H. (2020). Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors. European radiology, 30, 5525-5532.
Mertler, C. A., Vannatta, R. A., & LaVenia, K. N. (2021). Advanced and multivariate statistical methods: Practical application and interpretation. Routledge. http://bayes.acs.unt.edu:8083/BayesContent/class/Jon/ResourcesWkshp/DecisionTree_MertlerVannatta.pdf
Pandey, P., & Pandey, M. M. (2021). Research methodology tools and techniques. Bridge Center. http://dspace.vnbrims.org:13000/jspui/bitstream/123456789/4666/1/RESEARCH%20METHODOLOGY%20TOOLS%20AND%20TECHNIQUES.pdf
Alowais, S. A., Alghamdi, S. S., Alsuhebany, N., Alqahtani, T., Alshaya, A. I., Almohareb, S. N., Aldairem, A., Alrashed, M., Bin Saleh, K., Badreldin, H. A., Al Yami, M. S., Al Harbi, S., & Albekairy, A. M. (2023). Revolutionizing healthcare: the role of artificial intelligence in clinical practice. BMC Medical Education, 23, 689. https://doi.org/10.1186/s12909-023-03198-8
Bajwa, J., Munir, U., Nori, A., & Williams, B. (2021). Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc J, 8(2), e188–e194. https://doi.org/10.7861/fhj.2021-0095
Dave, M., & Patel, N. (2023). Artificial intelligence in healthcare and education. British Dental Journal, 234, 761–764. https://doi.org/10.1038/s41415-023-4001-9
Davenport, T., & Kalakota, R. (2019). The potential for artificial intelligence in healthcare. Future Healthc, 6(2), 94–98. https://doi.org/10.7861/futurehosp.6-2-94
