Official journal of the Slovak Society of Cardiology,
Slovak Society of Hypertension and Slovak Association for Cardiac Arrhythmias

Cardiology Letters 2018, 27(3):153-161

Artificial intelligence opens new horizons in science and medicine and offers sophisticated solutions to complex problems

El Hassoun O1, Valášková Z2, Hulín I2
1 Ústav histológie a embryológie LF UK v Bratislave
2 Ústav patologickej fyziológie LF UK v Bratislave, Slovenská republika

Published: March 1, 2018  Show citation

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El Hassoun O, Valášková Z, Hulín I. Artificial intelligence opens new horizons in science and medicine and offers sophisticated solutions to complex problems. Cardiology Letters. 2018;27(3):153-161.
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    References

    1. Hatala R, Hulín I. Reflexia XXII. kongresu Slovenskej kardiologickej spoločnosti v odpovediach profesora Hatalu. Cardiology Lett. 2017;26:313-318.
    2. Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism 2017;Apr,696S:S36-S40. doi: 10.1016/j.metabol.2017.01.011 Go to original source...
    3. Maeso S, Reza M, Mayol J, et al. Efficacy of the Da Vinci surgical system in abdominal surgery compared with that of laparoscopy: a systematic review and meta-analysis. Annals of Surgery 2010;252:254-262. Go to original source...
    4. Veverková L, Čapov I, Vlček P, et al. "State of art "robotické chirurgie. Endoskopie 2010;19(1):17-20.
    5. Yu J, Wang Y, Li Y, et al. The safety and effectiveness of Da Vinci surgical system compared with open surgery and laparoscopic surgery: a rapid assessment. Journal of Evidence-Based Medicine 2014;7:121-134. Go to original source...
    6. Banavar, G. Learning to trust artificial intelligence systems. Accountability, Compliance and Ethics in the Age of Smart Machines, IBM Global Services 2016.
    7. Kononenko I. Machine learning for medical diagnosis: history, state of the art and perspective. Artificial Intelligence in medicine 2001;23:89-109. Go to original source...
    8. Bennett CC, Hauser K. Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach. Artificial intelligence in medicine 2013;57:9-19. Go to original source...
    9. Weng SF, Reps J, Kai J, et al. Can machine-learning improve cardiovascular risk prediction using routine clinical data? PloS one 12.4 (2017): e0174944. Go to original source...
    10. Thagard P. Cognitive Science. The Stanford Encyclopedia of Philosophy (Fall 2014 Edition). URL = <https://plato.stanford.edu/archives/fall2014/entries/cognitive-science/>.
    11. McCann MT, Ozolek JA, Castro CA, et al. Automated histology analysis: Opportunities for signal processing. IEEE Signal Processing Magazine 2015;32:78-87. <https://plato.stanford.edu/archives/fall2014/entries/cognitivescience/>. Go to original source...
    12. Yun L, Gadepalli K, Norouzi M, et al. Detecting cancer metastases on gigapixel pathology images. arXiv preprint arXiv:1703.02442 (2017).
    13. Gershenwald JE, Scolyer RA, Hess KR, et al. Melanoma staging: Evidence-based changes in the American Joint Committee on Cancer eighth edition cancer staging manual. CA: a cancer journal for clinicians 2017;67:472-492. Go to original source...

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