Volume 11, Issue 4 (12-2023)
J Surg Trauma 2023, 11(4): 128-131 |
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Heydari S, Shaker Ardakani Y, Delzendeh M, Beigzadeh A. Artificial Intelligence (AI): applications and ethical issues with an emphasis on emergency medicine. J Surg Trauma 2023; 11 (4) :128-131
URL: http://jsurgery.bums.ac.ir/article-1-438-en.html
URL: http://jsurgery.bums.ac.ir/article-1-438-en.html
Artificial Intelligence (AI): applications and ethical issues with an emphasis on emergency medicine
Education Development Center, Sirjan School of Medical Sciences, Sirjan, Iran
Abstract: (652 Views)
- The emergence of “Artificial Intelligence” (AI) dates back to 1955. It is a broad term that refers to using computers to mimic human intelligence, such as decision-making, reasoning ability, generalization, etc. with minimal human intervention. AI technology is impacting our lives in many ways, from an education perspective to research and health care. For instance, in Emergency Medicine, AI is expected to significantly influence Emergency Medicine with its potential uses such as predicting patient outcomes, detecting early signs of deterioration through vital sign monitoring, and analyzing clinical images. In a similar vein, AI technology is used for a variety of medical purposes, including machine learning, robotics, medical diagnostics, medical statistics, and biology. In general, the world of medicine is undergoing major changes as the use of AI technology is advancing at a breakneck pace, from diagnosing diseases to manufacturing new drugs. To the best of our knowledge, the application of AI in medicine remains a hot topic of great interest to researchers and is constantly being developed and refined. However, the use of AI can have ethical concerns to consider. Here we touch on some practical aspects and ethical considerations of AI technology in medicine.
Type of Study: Letter to Editor |
Subject:
General
Received: 2024/06/19 | Accepted: 2024/07/2 | ePublished ahead of print: 2024/07/2 | Published: 2024/07/3
Received: 2024/06/19 | Accepted: 2024/07/2 | ePublished ahead of print: 2024/07/2 | Published: 2024/07/3
References
1. Jaakkola H, Henno J, Mäkelä J, Thalheim B. Artificial intelligence yesterday, today and tomorrow. In 2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) 2019; 860-867). [DOI:10.23919/MIPRO.2019.8756913]
2. Tahayori B, Chini-Foroush N, Akhlaghi H. Advanced natural language processing technique to predict patient disposition based on emergency triage notes. Emerg Med Australas. 2021; 33:480-484. [DOI:10.1111/1742-6723.13656]
3. Kishore K, Braitberg G, Holmes NE, Bellomo R. Early prediction of hospital admission of emergency department patients. Emerg Med Australas. 2023; 35: 572-588. [DOI:10.1111/1742-6723.14169]
4. Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017; 69: 36-40. [DOI:10.1016/j.metabol.2017.01.011]
5. Nagi F, Salih R, Alzubaidi M, Shah H, Alam T, Shah Z, et al. Applications of Artificial Intelligence (AI) in Medical Education: A Scoping Review. Healthcare Transformation with Informatics and Artificial Intelligence. 2023:648-651. [DOI:10.3233/SHTI230581]
6. Stewart J, Sprivulis P, Dwivedi G. Artificial intelligence and machine learning in emergency medicine. Emerg Med Australas. 2018;30(6):870-874. [DOI:10.1111/1742-6723.13145]
7. Zheng J, Lin D, Gao Z, Wang S, He M, Fan J. Deep learning assisted efficient AdaBoost algorithm for breast cancer detection and early diagnosis. IEEE Access. 2020; 8:96946-96954. [DOI:10.1109/ACCESS.2020.2993536]
8. Zhang P-I, Hsu C-C, Kao Y, Chen C-J, Kuo Y-W, Hsu S-L, et al. Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain. Scandinavian Journal of Trauma. Resuscitation and Emergency Medicine. 2020;28(1):1-7. [DOI:10.1186/s13049-020-00786-x]
9. Chen Y, Stewart JW, Ge J, Cheng B, Chekroud A, Hellerstein DJ. Personalized symptom clusters that predict depression treatment outcomes: A replication of machine learning methods. J Affect Disord Rep. 2023; 11:100470. [DOI:10.1016/j.jadr.2023.100470]
10. Chen Y-M, Chen P-C, Lin W-C, Hung K-C,Chen Y-CB, Hung C-F, et al. Predicting new-onset post-stroke depression from real-world data using machine learning algorithm. Front Psychiatry. 2023; 14:1195586. [DOI:10.3389/fpsyt.2023.1195586]
11. Choi JH, Kim H-A, Kim W, Lim I, Lee I, Byun BH, et al. Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning. Scientific reports. 2020; 10(1):21149. [DOI:10.1038/s41598-020-77875-5]
12. Hashimoto DA, Rosman G, Rus D, Meireles OR. Artificial Intelligence in Surgery: Promises and Perils. Ann Surg. 2018;268(1):70-76. [DOI:10.1097/SLA.0000000000002693]
13. Morley J, Machado CC, Burr C, Cowls J, Joshi I, Taddeo M, et al. The ethics of AI in health care: a mapping review. Social Science & Medicine. 2020; 260:113172. [DOI:10.1016/j.socscimed.2020.113172]
14. Krittanawong C, Zhang H, Wang Z, Aydar M, Kitai T. Artificial intelligence in precision cardiovascular medicine. J Am Coll Cardiol. 2017;69(21):2657-2664. [DOI:10.1016/j.jacc.2017.03.571]
15. Char DS, Shah NH, Magnus D. Implementing machine learning in health care-addressing ethical challenges. The New England journal of medicine. 2018; 378(11):981-983. [DOI:10.1056/NEJMp1714229]
16. Ghassemi M, Naumann T, Schulam P, Beam AL, Chen IY, Ranganath R. Practical guidance on artificial intelligence for health-care data. Lancet Digit Health. 2019; 1(4): 157-159. [DOI:10.1016/S2589-7500(19)30084-6]
17. Liu N, Zhang Z, Ho AF, Ong ME. Artificial intelligence in emergency medicine. J Emerg Crit Care Med (JECCM).2018;2(8);1-6. [DOI:10.21037/jeccm.2018.10.08]
18. Grant K, McParland A. Applications0 of artificial intelligence in emergency medicine. University of Toronto medical journal (UTMJ). 2019;96(1);37-39.
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