Artificial Intelligence (AI) represents a significant milestone in health care's digital transformation. However, traditional health care education and training often lack digital competencies. To promote safe and effective AI implementation, health care professionals must acquire basic knowledge of machine learning and neural networks, critical evaluation of data sets, integration within clinical workflows, bias control, and human-machine interaction in clinical settings. Additionally, they should understand the legal and ethical aspects of digital health care and the impact of AI adoption. Misconceptions and fears about AI systems could jeopardize its real-life implementation. However, there are multiple barriers to promoting electronic health literacy, including time constraints, overburdened curricula, and the shortage of capacitated professionals. To overcome these challenges, partnerships among developers, professional societies, and academia are essential. Integrating specialists from different backgrounds, including data specialists, lawyers, and social scientists, can significantly contribute to combating digital illiteracy and promoting safe AI implementation in health care.
Keywords: artificial intelligence; clinical; data; dataset; digital; digital education; digital health; education; evaluation; health education; machine learning; network; neural; set; transformation.
©Fernando Korn Malerbi, Luis Filipe Nakayama, Robyn Gayle Dychiao, Lucas Zago Ribeiro, Cleva Villanueva, Leo Anthony Celi, Caio Vinicius Regatieri. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.06.2023.