Challenges and Solutions for Artificial Intelligence Adoption in Healthcare – A Literature Review
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3311-2_6
Reference27 articles.
1. Amann, J., Blasimme, A., Vayena, E., et al.: Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC Med. Inform. Decis. Mak. 20, 310 (2020). https://doi.org/10.1186/s12911-020-01332-6
2. Babel, A., Taneja, R., Mondello Malvestiti, F., Monaco, A., Donde, S.: Artificial intelligence solutions to increase medication adherence in patients with non-communicable diseases. Front. Digit. Health 3 (2021). https://doi.org/10.3389/fdgth.2021.669869
3. Barredo Arrieta, A., et al.: Explainable Artificial Intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Int. J. Inf. Fusion 58, 82–115 (2020). https://doi.org/10.1016/j.inffus.2019.12.012
4. Bohr, A., Memarzadeh, K. (eds.): Artificial Intelligence in Healthcare. Academic Press (2020)
5. Choudhury, A., Asan, O.: Impact of accountability, training, and human factors on the use of artificial intelligence in healthcare: exploring the perceptions of healthcare practitioners in the US. Hum. Factors Healthc. 2(100021), 100021 (2022). https://doi.org/10.1016/j.hfh.2022.100021
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