Table 1.

Demographics, AI usage, and education status of participants

Gender, n (%)
Male	93 (63.3%)
Female	54 (36.7%)
Age, median (IQR)	39 (35–46)
Years as physician, median (IQR)	14 (10–22)
Years in oncology, median (IQR)	5 (2–14)
Site of practice, n (%)
University hospital	70 (47.6%)
Training and research hospital	46 (31.3%)
Private hospital	20 (13.6%)
State hospital	8 (5.4%)
Private clinic	3 (2.0%)
Educational and academic status, n (%)
Resident, fellow	56 (38.1%)
Specialist	33 (22.4%)
Professor	31 (21.1%)
Associate professor	24 (16.3%)
Assistant professor	3 (2.0%)
Used any artificial intelligence before, n (%)*
ChatGPT and other GPT models	114 (77.5%)
Google Gemini	25 (17.0%)
Microsoft Bing	16 (10.9%)
Others**	13 (8.8%)
Have not used any	33 (22.5%)
Artificial intelligence education status, n (%)
Not received any education	133 (90.5%)
Received basic-level education	10 (6.8%)
Received advanced-level education	3 (2.0%)
Received intermediate-level education	1 (0.7%)
Will to receive education for artificial intelligence, n (%)
Yes	139 (94.6%)
No	8 (5.4%)
Resources used to acquire knowledge about artificial intelligence, n (%)*
Colleagues	39 (26.5%)
Academic publications	34 (23.1%)
Online courses and websites (e.g., Coursera, EDx)	32 (21.8%)
Popular science publications	29 (19.7%)
Conferences and workshops	27 (18.4%)
Other periodicals	7 (4.8%)
Others***	8 (5.4%)
Do not using any resources	57 (38.8%)

^*Percentages shown for total participant counts

^**Other artificial intelligences, include Meta LLAMA, X Grok, Google Bard, Perplexity, Anthropic Claude

^***Other resources include social media and non-academic books

IQR Interquartile range