Paper
24 March 2023 Prospects and ethical issues of artificial intelligence in medicine
Qianyu Liang
Author Affiliations +
Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126110K (2023) https://doi.org/10.1117/12.2669474
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom
Abstract
Artificial intelligence is being used more and more widely within the medical field. In its application, it also falls into two main categories. One category is simulation through the application of computer algorithms, and the other is also the application of the evolving science of solid state physics. The application of algorithms is generally to help doctors diagnose conditions or predict them, for example. The applications of physics are similar to some of the advanced medical devices available today. For example, some medical instruments when used for minimally invasive surgery fall into this category. The development of artificial intelligence is certainly a good thing for human medicine and could significantly advance the medical community. However, the existence of artificial intelligence has been controversial and has been at the forefront of moral and ethical debate. This paper will discuss this topic through the existing literature, simple data simulations and other methods. Ultimately, it is concluded that the development of artificial intelligence in the medical field has very good prospects to improve the efficiency of medical care while reducing the cost of access and providing a great livelihood project.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Qianyu Liang "Prospects and ethical issues of artificial intelligence in medicine", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126110K (24 March 2023); https://doi.org/10.1117/12.2669474
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KEYWORDS
Artificial intelligence

Medicine

Data modeling

Biomedical applications

Evolutionary algorithms

Heart

Cardiovascular disorders

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