AI-driven patient-centered care: A digital transformation framework for gynecologic cancer genetic counseling

人工智能驱动的以患者为中心的医疗服务:妇科癌症遗传咨询的数字化转型框架

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Abstract

ObjectivesThis study evaluates artificial intelligence (AI) reasoning capabilities in gynecologic cancer genetic counseling, comparing the performance of ChatGPT and DeepSeek models to guide patient-centered AI implementation in clinical genetics.MethodsUsing 40 National Comprehensive Cancer Network-aligned counseling scenarios, we conducted blinded dual-oncologist evaluations of two large language models. Methodological rigor included model anonymization, a pre-calibrated scoring framework, and validated metrics (Global Quality Scale and Patient Education Materials Assessment Tool) assessing informational coherence, understandability, and actionability.ResultsDeepSeek demonstrated superior informational breadth (mean character difference: -609.0, p < .0001) and visual communication (diagram integration, p < .01), with 49-fold greater probability in recommending clear and actionable actions (p < .01, OR = 49.0). ChatGPT excelled in concise summarization (22% faster response generation, p = .013).ConclusionStrategic AI model selection-leveraging DeepSeek's visually-rich, structured educational approach for complex information, and ChatGPT's concise, rapid summarization for efficient communication-enhances patient-centered genetic education when combined with clinician oversight. This framework supports healthcare's digital transformation by optimizing human-AI collaboration in hereditary cancer care.

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