References
- Donabedian A. Evaluating the quality of medical care. Milbank Q. 2005;83(4):691–729.
- Jefford M, Stockler MR, Tattersall MHN. Outcomes research: what is it and why does it matter? Intern Med J. 2003;33(3):110–118.
- In H, Rosen JE. Primer on outcomes research. J Surg Oncol. 2014;110(5):489–493.
- Outcome Assessment, Health Care - MeSH - NCBI [Internet]. Natl. Cent. Biotechnol. Inf. 1992 [cited 2020 May 8]. Available from: https://www.ncbi.nlm.nih.gov/mesh/68017063.
- Bridges JFP, Jones C. Patient-based health technology assessment: a vision of the future. Int J Technol Assess Health Care. 2007;23(1):30–35.
- Jönsson B, Hampson G, Michaels J, et al., Advanced therapy medicinal products and health technology assessment principles and practices for value-based and sustainable healthcare. Eur J Heal Econ. 2019;20(3): 427–438.
- Matheny ME, Whicher D, Thadaney Israni S Artificial intelligence in health care: a report from the national academy of medicine. JAMA - J. Am. Med. Assoc. American Medical Association; 2020;509–510.
- Lachance CC, Walter M. Artificial intelligence for classification of lung nodules: a review of clinical utility, diagnostic accuracy, cost-effectiveness, and guidelines. In: Artif. intell. classif. lung nodules a rev. clin. util. diagnostic accuracy, cost-effectiveness, guidel. Ottawa: Canadian Agency for Drugs and Technologies in Health; 2020.
- Ramesh AN, Kambhampati C, Monson JRT, et al. Artificial intelligence in medicine. Ann R Coll Surg Engl. 2004;86(5):334–338. .
- Hamet P, Tremblay J. Artificial intelligence in medicine. Metabolism. 2017;69:S36–S40.
- Chartrand G, Cheng PM, Vorontsov E, et al. Deep learning: a primer for radiologists. Radiographics. 2017;37(7):2113–2131. .
- Meskó B, Görög M. A short guide for medical professionals in the era of artificial intelligence. NPJ Digit Med. 2020;3(1):126.
- Wahl B, Cossy-Gantner A, Germann S, et al. Artificial intelligence (AI) and global health: how can AI contribute to health in resource-poor settings? BMJ Glob Heal. 2018;3(4):e000798. .
- Capone A, Cicchetti A, Mennini FS, et al. Health Data Entanglement and artificial intelligence-based analysis: a brand new methodology to improve the effectiveness of healthcare services. Clin Ter. 2016;167(5):e102–e111. .
- Magrabi F, Ammenwerth E, McNair JB, et al. Artificial intelligence in clinical decision support: challenges for evaluating ai and practical implications. Yearb Med Inform. 2019;28(1):128–134. .
- Naylor CD. On the prospects for a (Deep) learning health care system. J Am Med Assoc. 2018;320(11):1099–1100.
- Mason J, Morrison A, Visintini S An overview of clinical applications of artificial intelligence. Can. Agency Drugs Technol. Heal. Ottawa; 2018.
- Ben-Israel D, WB J, Casha S, et al. The impact of machine learning on patient care: a systematic review. In: Artif Intell Med. 2020;103.
- Liu X, Faes L, Kale AU, et al. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis. Lancet Digit Heal. 2019;1(6):e271–e297.
- Alami H, Lehoux P, Auclair Y, et al. Artificial intelligence and health technology assessment: anticipating a new level of complexity. J Med Internet Res. 2020;22(7):e17707. JMIR Publications.
- Rajkomar A, Oren E, Chen K, et al. Scalable and accurate deep learning with electronic health records. NPJ Digit Med. 2018 ;1:18.
- Courville IG. YB and A. Deep Learning. Cambridge: MIT Press; 2016.
- Maddox TM, Rumsfeld JS, Payne PRO. Questions for artificial intelligence in health care. J Am Med Assoc. 2019;321(1):31–32.
- Christodoulou E, Ma J, Collins GS, et al. A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models. J Clin Epidemiol. 2019;110:12–22.
- Buchlak QD, Esmaili N, Leveque JC, et al. Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review. Neurosurg Rev. 2020;43(5):1235–1253.
- Schardt C, Adams MB, Owens T, et al. Utilization of the PICO framework to improve searching PubMed for clinical questions. BMC Med Inform Decis Mak. 2007;7:7.
- World Health Organization. ICD-11 for Mortality and Morbidity Statistics [Internet]. Geneva; 2018. Available from: https://www.who.int/classifications/icd/en/.
- Brownlee J Supervised and unsupervised machine learning algorithms [internet]. Mach. Learn. Mastery. 2016 [cited 2020 May 8]. Available from: https://machinelearningmastery.com/supervised-and-unsupervised-machine-learning-algorithms/.
- Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLOS Med. 2009;6(7):e1000097. .
- Jiang F, Jiang Y, Zhi H, et al. Artificial intelligence in healthcare: past, present and future. Stroke Vasc Neurol.. 2017;2(4):230–243.
- Vartanian TP. Secondary data analysis. New York: Oxford University Press; 2011.