Research Repository
On this page we present a list of references to some peer reviewed journal articles from the medical literature highlighting the wide acceptance and use of artificial intelligence in healthcare, including nephrology and other areas.
Medical Literature
1. Niel O, Bastard P. Artificial intelligence in nephrology: core concepts, clinical applications, and perspectives. American Journal of Kidney Diseases. 2019 Dec 1;74(6):803-10.
2. Badrouchi S, Bacha MM, Hedri H, Ben Abdallah T, Abderrahim E. Toward generalizing the use of artificial intelligence in nephrology and kidney transplantation. Journal of Nephrology. 2022 Dec 22:1-4.
3. Xie G, Chen T, Li Y, Chen T, Li X, Liu Z. Artificial intelligence in nephrology: How can artificial intelligence augment nephrologists’ intelligence?. Kidney Diseases. 2020;6(1):1-6.
4. Loftus TJ, Shickel B, Ozrazgat-Baslanti T, Ren Y, Glicksberg BS, Cao J, Singh K, Chan L, Nadkarni GN, Bihorac A. Artificial intelligence-enabled decision support in nephrology. Nature Reviews Nephrology. 2022 Jul;18(7):452-65.
5. Lemley KV. Machine learning comes to nephrology. Journal of the American Society of Nephrology. 2019 Oct 1;30(10):1780-1.
6. Li Q, Fan QL, Han QX, Geng WJ, Zhao HH, Ding XN, Yan JY, Zhu HY. Machine learning in nephrology: scratching the surface. Chinese Medical Journal. 2020 Mar 20;133(06):687-98.
7. Junior GS, Askari M, Oliveira J. Digital health and possible solutions to improve the care in the field of nephrology. Nephrology and Public Health Worldwide. 2021;199:307-21.
8. Niel O, Bastard P, Boussard C, Hogan J, Kwon T, Deschênes G. Artificial intelligence outperforms experienced nephrologists to assess dry weight in pediatric patients on chronic hemodialysis. Pediatric Nephrology. 2018 Oct;33:1799-803.
9. Nadkarni GN. Introduction to Artificial Intelligence and Machine Learning in Nephrology. Clinical Journal of the American Society of Nephrology. 2023:10-2215.
10. Shickel B, Loftus TJ, Ren Y, Rashidi P, Bihorac A, Ozrazgat-Baslanti T. Digital Health Transformers and Opportunities for Artificial Intelligence–Enabled Nephrology. Clinical Journal of the American Society of Nephrology. 2023 Apr 1;18(4):527-9.
11. Chiu YL, Jhou MJ, Lee TS, Lu CJ, Chen MS. Health data-driven machine learning algorithms applied to risk indicators assessment for chronic kidney disease. Risk Management and Healthcare Policy. 2021 Oct 27:4401-12.
12. Miao J, Thongprayoon C, Cheungpasitporn W. Assessing the Accuracy of ChatGPT on Core Questions in Glomerular Disease. Kidney International Reports. 2023 May 26.
13. Tsai YT, Yang FJ, Lin HM, Yeh JC, Cheng BW. Constructing a prediction model for physiological parameters for malnutrition in hemodialysis patients. Scientific Reports. 2019 Jul 24;9(1):10767.
14. Milecki L, Kalogeiton V, Bodard S, Anglicheau D, Correas JM, Timsit MO, Vakalopoulou M. MEDIMP: Medical Images and Prompts for renal transplant representation learning. arXiv preprint arXiv:2303.12445. 2023 Mar 22.
15. Cohen TA, Patel VL, Shortliffe EH, editors. Intelligent Systems in Medicine and Health: The Role of AI. Springer Nature; 2022 Nov 9.
16. Argenson A, Devi-Chou V. Artificial intelligence in healthcare. In Principles of Gender-Specific Medicine 2023 Jan 1 (pp. 601-618). Academic Press.
17. Dorr DA, Adams L, Embí P. Harnessing the Promise of Artificial Intelligence Responsibly. JAMA. 2023 Apr 25;329(16):1347-8.
18. Brownstein JS, Rader B, Astley CM, Tian H. Advances in Artificial Intelligence for Infectious-Disease Surveillance. New England Journal of Medicine. 2023 Apr 27;388(17):1597-607.
19. Singhal K, Tu T, Gottweis J, Sayres R, Wulczyn E, Hou L, Clark K, Pfohl S, Cole-Lewis H, Neal D, Schaekermann M. Towards Expert-Level Medical Question Answering with Large Language Models. arXiv preprint arXiv:2305.09617. 2023 May 16.
20. Nori H, King N, McKinney SM, Carignan D, Horvitz E. Capabilities of gpt-4 on medical challenge problems. arXiv preprint arXiv:2303.13375. 2023 Mar 20.