This study investigates the factors influencing trust and acceptance of AI-powered medical technologies and assesses their relevance among key stakeholders. A rapid literature review identified 110 factors related to trust and 77 factors related to acceptance, which were categorized into four groups: human-related, technology-related, ethical and legal, and additional factors. An electronic survey was conducted with 22 participants from various stakeholder groups, including researchers, technology providers, hospital staff, and policymakers. The survey results showed that 84% of the factors were considered highly relevant to trust and acceptance, while patient gender, age, and education level were found to be of low relevance. The study highlights the importance of factors such as the knowledge and understanding of AI among healthcare professionals, transparency, and the balance of risks and benefits in building trust and acceptance. The findings can help implementers of medical AI applications to understand and address the concerns of stakeholders, facilitating the successful adoption and implementation of AI in healthcare.This study investigates the factors influencing trust and acceptance of AI-powered medical technologies and assesses their relevance among key stakeholders. A rapid literature review identified 110 factors related to trust and 77 factors related to acceptance, which were categorized into four groups: human-related, technology-related, ethical and legal, and additional factors. An electronic survey was conducted with 22 participants from various stakeholder groups, including researchers, technology providers, hospital staff, and policymakers. The survey results showed that 84% of the factors were considered highly relevant to trust and acceptance, while patient gender, age, and education level were found to be of low relevance. The study highlights the importance of factors such as the knowledge and understanding of AI among healthcare professionals, transparency, and the balance of risks and benefits in building trust and acceptance. The findings can help implementers of medical AI applications to understand and address the concerns of stakeholders, facilitating the successful adoption and implementation of AI in healthcare.