An Investigation Into the Comprehension, Perceptions, Application, and Determinants Affecting the Utilization of Deepseek Artificial Intelligence by Healthcare Professionals: A Cross-Sectional Study.

Background and Objective: DeepSeek LLM, launched on January 5, 2024, integrates natural language processing, data analytics, and medical picture analysis. The use of it among frontline healthcare personnel in Western China has not been previously examined. This study evaluates Chengdu clinicians' knowledge, attitudes, and usage habits on DeepSeek while identifying significant impacting factors. Methods: A WeChat-based survey was administered to physicians, nurses, medical technicians, and administrative personnel at two tertiary maternity and pediatric hospitals in Chengdu from February 24 to 26, 2025. The gathered data encompassed demographics, educational attainment, job designation, familiarity with DeepSeek, frequency of use, openness to training, and preferred functionalities. Of the 865 distributed questionnaires, 788 valid replies (91.10%) were analyzed using SPSS 25. Group disparities were analyzed using chi-square tests, and forward likelihood-ratio logistic regression determined predictors of awareness, utilization, and willingness to undergo training (p < 0.05). Results: A total of 94.2% of participants indicated awareness of DeepSeek, predominantly via media sources (83.65%) and peer endorsements (49.53%). Usage was indicated by 76.14% of respondents, comprising 98.6% of physicians and 89.61% of individuals with a master's degree or higher. The desire to train attained 87.44%, with predominant preferences for hands-on practice (99.4%), a platform overview (93.1%), and case study talks (90.4%). Univariate analyses revealed substantial disparities in awareness, utilization, and training interest based on education level, job title, and job type (p < 0.05). Logistic analysis indicated that possessing a master's degree or higher significantly enhanced the likelihood of awareness (OR: 8.36; 95% CI: 1.13-61.87; p < 0.05). Clinicians aged 51 and older exhibited a reduced likelihood of utilizing DeepSeek (OR: 0.29; 95% CI: 0.13-0.64; p < 0.05). Individuals with mid-level professional titles demonstrated increased utilization (OR: 4.08; p < 0.001) and a greater readiness to undergo training (OR: 13.26; p < 0.001), while those holding a bachelor's degree showed a reduced inclination to engage in training (OR: 0.47; p < 0.05). Conclusion: There were substantial deficiencies in the awareness and utilization of DeepSeek among healthcare professionals in Chengdu. Educational attainment, professional status, and occupation significantly influence outcomes. Customized training and assistance are essential to facilitate wider and more successful implementation.