Artificial Intelligence: Adaptation Into Current Biomedical Engineering and Its Coefficient of Difficulty?
DOI:
https://doi.org/10.61173/s3hvwf19Keywords:
artificial intelligence, biomedical engineeringAbstract
Artificial Intelligence (AI) is a gigantic, developing subject used comprehensively in the continuous period of Biomedical Engineering, where scientists are investigating all the purposes of artificial intelligence and contemplating how to foster it. The accuracy of AI is enhanced through daily improvement, and the current prediction using AI is evaluated by its accuracy in this literature review. The present achievement of AI in healthcare is discussed with future applications. As AI is an arising innovation, its downsides are inevitable and considered. This review summarizes the unsolved questions and difficulties clinics and engineers face individually.
References
[1] Pavel Hamet, Johanne Tremblay, Artificial intelligence in medicine, Metabolism, Volume 69, Supplement, 2017, Pages S36-S40, ISSN 0026-0495,
[2] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S., Ballard, A. J., Cowie, A., Romera-Paredes, B., Nikolov, S., Jain, R., Adler, J., Back, T., … Hassabis, D. (2021). Applying and improving AlphaFold at CASP14. Proteins, 89(12), 1711–1721.
[3] Senior, A.W., Evans, R., Jumper, J. et al. Improved protein structure prediction using potentials from deep learning. Nature 577, 706–710 (2020).
[4] Michel Dupuis, Léo Delbos, Raphael Veil, Catherine Adamsbaum, External validation of a commercially available deep learning algorithm for fracture detection in children, Diagnostic and Interventional Imaging, Volume 103, Issue 3, 2022, Pages 151-159, ISSN 2211-5684,
[5] Hameed, Bm & Prerepa, Gayathri & Patil, Dr & Shekhar, Pranav & Raza, Syed & Karimi, Hadis & Paul, Rahul & Naik, Nithesh & Modi, Sachin & Vigneswaran, Ganesh & Rai, Bhavan & Chlosta, Piotr & Somani, Bhaskar. (2021). Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future. Therapeutic Advances in Urology. 13. 175628722110448. 10.1177/17562872211044880.
[6] Lakhani, P. & Sundaram, B. Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks. Radiology 284, 574– 582 (2017).
[7] Health IT Analytics, March 2022, Arguing the Pros and Cons of Artificial Intelligence in Healthcare, https://healthitanalytics. com/news/arguing-the-pros-and-cons-of-artificial-intelligencein-healthcare
[8] Drexel University College of Computing and Informatics, July 2021, Pros & Cons of Artificial Intelligence in Medicine, https://drexel.edu/cci/stories/artificial-intelligence-in-medicinepros-and-cons/
[9] Choi, Y.S., Yin, R.T., Pfenniger, A. et al. Fully implantable and bioresorbable cardiac pacemakers without leads or batteries. Nat Biotechnol 39, 1228–1238 (2021).
[10] O’Sullivan S, Nevejans N, Allen C, et al. Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery. Int J Med Robotics Comput Assist Surg. 2019;15:e1968
[11] Basu K, Sinha R, Ong A, Basu T. Artificial Intelligence: How is It Changing Medical Sciences and Its Future? Indian J Dermatol. 2020 Sep-Oct;65(5):365-370.
[12] Industry Today. (2020, September 17). Five challenges of implementing AI in manufacturing. Retrieved August 26, 2022
[13] Simulation/IT. (2021, March 1). The six challenges of Dean&Francis implementing AI in manufacturing. Retrieved August 26, 2022
[14] Jiang, L., Wu, Z., Xu, X., Zhan, Y., Jin, X., Wang, L., & Qiu, Y. (2021). Opportunities and challenges of artificial intelligence in the medical field: Current application, emerging problems, and problem-solving strategies. Journal of International Medical Research, 49(3), 030006052110001
[15] Kelly, C. J., Karthikesalingam, A., Suleyman, M., Corrado, G., & King, D. (2019). Key challenges for delivering clinical impact with Artificial Intelligence. BMC Medicine, 17(1).
[16] Anton. (2022, May 11). Ai challenges in healthcare: What we should be aware of. Retrieved August 26, 2022
Downloads
Published
Issue
Section
License
Copyright (c) 2023 by the authors.
This work is licensed under a Creative Commons Attribution 4.0 International License.
