Healthcare Transformation: Artificial Intelligence's Transformative Impact in Medical Imaging and Diagnosis
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Abstract: AI is changing the way medical imaging and analysis are done, which is transforming healthcare. AI is improving the speed, accuracy, and efficiency of finding diseases, diagnosing them, and planning treatments by helping those analyze huge amounts of data. Deep learning and machine learning are both AI-powered technologies that are making radiology and imaging-based diagnostics better. They also make early disease identifying and personalized medicine possible. This paper talks about AI’s present and future potential role in medical imaging and evaluation, focusing on its uses, advantages, and difficulties. Radiology and pathology are being revolutionized by AI, from picture identification and analysis to automated image segmentation and categorization. AI is also making predictive analytics, finding new drugs, and virtual health helpers better. AI could completely change healthcare, but there are some problems that need to be fixed before it can be used widely. These include limited data, rule- based issues, moral concerns, and problems with integrating AI with other systems. As AI technology improves, it will continue to improve medical decisions and patient care around the world. This will make the healthcare system more efficient and improve patient results.
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References
Lambin P, Rios- Velazquez E, Leijenaar R, Carvalho S, van Stiphout RGPM, Granton P, et al. Radiomics: extracting more information from medical images using
Thompson RF, Valdes G, Fuller CD, Carpenter CM, Morin O, Aneja S, et al. Artificial intelligence in radi- ation oncology imaging. Int J Radiat Oncol Biol Phys 2018; 102: 1159–61. doi: https://doi.org/10.1016/j. ijrobp.2018.05.070
Hitaj B. Deep models under the GAN: information leakage from collaborative deep learning. Cryptogra- phy and Security 2017; arXiv–1702.
Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJWL. Artificial intelligence in radiology. Nat Rev Cancer 2018; 18: 500–10. doi: https://doi.org/10. 1038/s41568-018-0016-5
Pesapane F, Codari M, Sardanelli F. Artificial intel- ligence in medical imaging: threat or opportunity? Radiologists again at the forefront of innovation in medicine.
Coelho, L. (2023). How Artificial Intelligence Is Shap- ing Medical Imaging Technology: A Survey of Inno- vations and Applications. In Bioengineering (Vol. 10, Issue 12, p. 1435). Multidisciplinary Digital Publishing Institute. https://doi.org/10.3390/bioengineering10121435.

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