https://orcid.org/0000-0003-1351-8442
References
- Lv J, Deng S, Zhang L. A review of artificial intelligence applications for antimicrobial resistance. Biosaf Health. 2021;3(1):22–31. doi:10.1016/j.bsheal.2020.08.003
- World Health Organization. Antimicrobial resistance. Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance. Accessed December 2, 2021.
- Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthc J. 2019;6(2):94–98. doi:10.7861/futurehosp.6-2-94
- World Health Organization. Antimicrobial stewardship programmes in health-care facilities in low- and middle-income countries. A practical toolkit. Available from: https://apps.who.int/iris/bitstream/handle/10665/329404/9789241515481-eng.pdf. Accessed December 2, 2021.
- Centers for Disease Control and Prevention. Antibiotic resistance threats in the United States; 2019. Available from: https://www.cdc.gov/drugresistance/pdf/threats-report/2019-ar-threats-report-508.pdf. Accessed December 2, 2021.
- Stokes JM, Yang K, Swanson K, et al. A deep learning approach to antibiotic discovery. Cell. 2020;180(4):688–702.e13. doi:10.1016/j.cell.2020.01.021
- Das P, Sercu T, Wadhawan K, et al. Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations. Nat Biomed Eng. 2021;5(6):613–623. doi:10.1038/s41551-021-00689-x
- Clinical Laboratory Standards Institute. Performance Standards for Antimicrobial Disk Susceptibility Tests; Approved Standard. 12th ed. Wayne, PA: Clinical Laboratory Standards Institute; 2015.
- Shao L, Zhu F, Li X. Transfer learning for visual categorization: a survey. IEEE Trans Neural Netw Learn Syst. 2015;26(5):1019–1034. doi:10.1109/tnnls.2014.2330900
- Smith NM, Lenhard JR, Boissonneault KR, et al. Using machine learning to optimize antibiotic combinations: dosing strategies for meropenem and polymyxin B against carbapenem-resistant Acinetobacter baumannii. Clin Microbiol Infect. 2020;26(9):1207–1213. doi:10.1016/j.cmi.2020.02.004
- Abdulla A, Wang B, Qian F, et al. Project IDentif.AI: harnessing artificial intelligence to rapidly optimize combination therapy development for infectious disease intervention. Adv Therap. 2020;3(7):2000034. doi:10.1002/adtp.202000034
- Brill MJE, Kristoffersson AN, Zhao C, Nielsen EI, Friberg LE. Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations. Clin Microbiol Infect. 2018;24(7):697–706. doi:10.1016/j.cmi.2017.11.023
- Montavon G, Samek W, Müller K-R. Methods for interpreting and understanding deep neural networks. Digit Signal Process. 2018;73:1–15. doi:10.1016/j.dsp.2017.10.011
- Ribeiro MT, Singh S, Guestrin C. “Why Should I Trust You?”: Explaining the predictions of any classifier. Paper presented at: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining; San Francisco, California, USA; 2016. doi: 10.1145/2939672.2939778.