Artificial Intelligence, Machine Learning and Medical Applications
PDF
Cite
Share
Request
Invited Paper
P: 1-6
March 2022

Artificial Intelligence, Machine Learning and Medical Applications

J Ankara Univ Fac Med 2022;75(1):1-6
1. Ankara Üniversitesi Mühendislik Fakültesi, Elektrik-Elektronik Mühendisliği Anabilim Dalı, Ankara, Türkiye
2. Ankara Üniversitesi Tıp Fakültesi, Göğüs Cerrahisi Anabilim Dalı, Ankara, Türkiye
3. Ankara Üniversitesi Medikal Tasarım ve Uygulama Merkezi (MEDITAM), Ankara, Türkiye
No information available.
No information available
Received Date: 11.11.2022
Accepted Date: 23.11.2022
Publish Date: 18.01.2023
PDF
Cite
Share
Request

ABSTRACT

Artificial intelligence (AI) is a science that is commonly used in daily life where the number and variety of application areas are constantly increasing. However, for an ordinary person, AI is perceived as robots/machines that will take away their jobs. Therefore, it is of utmost importance that the concept of AI is well understood, an awareness is raised and there is more to gain from AI than lose. Medical Science that has been serving the humanity since the existence is another area that AI is increasingly used. In this article, basic concepts pertaining to AI and machine learning are explained and the contributions that AI can provide to medicine and medical education have been revealed.

Keywords: Artificial Intelligence, Machine Learning, Artificial Intelligence In Medicine

References

1
Rouhiainen L. Artificial Intelligence: 101 things you must know today about our future, 2018.
2
Masters K. Artificial intelligence in medical education. Med Teach. 2019;41:976-980.
3
Turing AM. Computing machinery and intelligence. Mind. 1950;250:433-460.
4
Homage to John McCarthy, the Father of Artificial Intelligence (AI), https://www.artificial-solutions.com/blog/homage-to-john-mccarthy-the-father-of-artificial-intelligence(son erişim 3 Ekim 2022).
5
The Quartz guide to artificial intelligence: What is it, why is it important, and should we be afraid?,https://qz.com/1046350/the-quartz-guide-to-artificial-intelligence-what-is-it-why-is-it-important-and-should-we-be-afraid/(son erişim 3 Ekim 2022).
6
McCarthy, J.What is Artificial Intelligence?, http://jmc.stanford.edu/articles/whatisai/whatisai.pdf (son erişim 3 Ekim 2022).
7
Huempfer, S., 100 things machines learned to do this year, 2017. https://medium.com/echobox/100-things-machines-learnt-to-do-this-year-80b727a64231 (son erişim 3 Ekim 2022).
8
https://www.statista.com/statistics/871513/worldwide-data-created/(son erişim 3 Ekim 2022).
9
https://cbddo.gov.tr/SharedFolderServer/Genel/File/TR-UlusalYZStratejisi2021-2025.pdf(son erişim 3 Ekim 2022).
10
Mitchell, TM., Machine Learning, 1997, New York: McGraw-hill.
11
Çakır U. Ergitme Fırınlarında Optimum Sistem Parametrelerinin Pekiştirmeli Öğrenme Metodları ile Saptanması. 2022, Yüksek Lisans Tezi, Ankara Üniversitesi.
12
O’Neil C. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy, 2017, Penguin Books.
13
Gunning, D. Explainable artificial intelligence (XAI),2017, Technical Report, Defense Advanced ResearchProjects Agency (DARPA)
14
Schmelzer R. Understanding Explainable AI, 2019, https://www.forbes.com/sites/cognitiveworld/2019/07/23/understanding-explainable-ai/?sh=324a3d267c9e(son erişim 3 Ekim 2022).
15
Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines, 2019, NatureMachine Intelligence, Vol. 1 No. 9, pp. 389-399.
16
Park SH, Do KH, Kim S, et al. What should medical students know about artificial intelligence in medicine? J Educ Eval Health Prof. 2019;16:18.
17
Cangir AK, Orhan K, Kahya Y, et al. A CT-Based Radiomic Signature for the Differentiation of Pulmonary Hamartomas from Carcinoid Tumors. Diagnostics (Basel). 2022;12:416.
18
Gürsoy Çoruh A, Yenigün B, Uzun Ç, et al. A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification. Br J Radiol. 2021;94:20210222.
19
Kayi Cangir A, Orhan K, Kahya Y, et al. CT imaging-based machine learning model: a potential modality for predicting low-risk and high-risk groups of thymoma: “Impact of surgical modality choice”. World J Surg Oncol. 2021;19:147.
2024 ©️ Galenos Publishing House