Table 1.

Relevant issues and main specific items.

RELEVANT ISSUES	MAIN SPECIFIC ITEMS
ETHICAL ISSUES	Could the algorithm be used maliciously? What are the possible biases in the developed system? Have techniques been used to optimize the fairness of the system?
LEGAL ISSUES	Has the issue of patient privacy been addressed? How is cybersecurity managed? Is the algorithm open or protected?
EDUCATION AND IMPLEMENTATION	Have implementation strategies in clinical practice been studied? What are the main roadblocks of the system in its possible implementation in clinical practice? How should healthcare professionals be trained to use the new system?
QUALITY OF DATA	What is the quality of exploited data? Is the quality of data collected and analyzed demonstrable? Have transparent data transformation techniques been used?
CLINICAL APPLICATION	Is the algorithm applicable in real clinical practice? Does the algorithm require particular instruments/software/digitization processes to be applied? Has the proposed algorithm been externally validated? Does the model employ interpretable AI techniques?

Legend. Relevant challenges to the use of AI techniques in medicine are reported. Next to them, some of the main specific items that are essential to developing tests or using an AI-based clinical decision support system are listed. These issues should be addressed or researched whenever an AI tool for healthcare is created or implemented in clinical practice, respectively (AI = Artificial Intelligence).