Artificial intelligence in the medical physics community: An international survey

Purpose: To assess current perceptions, practices and education needs pertaining to artificial intelligence (AI) in the medical physics field. Methods: A web-based survey was distributed to the European Federation of Organizations for Medical Physics (EFOMP) through social media and email membership list. The survey included questions about education, personal knowledge, needs, research and professionalism around AI in medical physics. Demographics information were also collected. Responses were stratified and analysed by gender, type of institution and years of experience in medical physics. Statistical significance (p < 0.05) was assessed using paired t-test. Results: 219 people from 31 countries took part in the survey. 81% (n = 177) of participants agreed that AI will improve the daily work of Medical Physics Experts (MPEs) and 88% (n = 193) of respondents expressed the need for MPEs of specific training on AI. The average level of AI knowledge among participants was 2.3 +/- 1.0 (mean +/- standard deviation) in a 1-to-5 scale and 96% (n = 210) of participants showed interest in improving their AI skills. A significantly lower AI knowledge was observed for female participants (2.0 +/- 1.0), compared to male responders (2.4 +/- 1.0). 64% of participants indicated that they are not involved in AI projects. The percentage of female leading AI projects was significantly lower than the male counterparts (3% vs 19%). Conclusions: AI was perceived as a positive resource to support MPEs in their daily tasks. Participants demonstrated a strong interest in improving their current AI-related skills, enhancing the need for dedicated training for MPEs.

Automated summary

The survey results indicated that 81% of participants believed that AI would improve the daily work of Medical Physics Experts, and 88% expressed the need for specific training on AI. Participants showed an average level of AI knowledge at 2.3, with 96% interested in enhancing their AI skills. Females had significantly lower AI knowledge compared to males, and 64% of participants were not involved in AI projects.