Integrating Artificial Intelligence and Point-of-Care Ultrasound Within the Clinical-Scientific Method: A Framework for Safer, Smarter Medicine

将人工智能和床旁超声技术融入临床科学方法:构建更安全、更智能的医疗框架

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Abstract

This article proposes a novel integrative framework that unifies the clinical method and the scientific method as parallel processes of knowledge generation and decision-making, positioning point-of-care ultrasound (POCUS) and artificial intelligence (AI) as complementary extensions of the clinician's senses and reasoning that enhance diagnostic accuracy while preserving human judgment. The framework describes how experience and evidence interact through observation, hypothesis generation, testing, and revision, and illustrates how POCUS improves bedside diagnostic precision while AI supports data integration and interpretation. The central takeaway is that integrating AI and POCUS within the clinical-scientific method enables more structured interpretation of clinical data, reduces diagnostic uncertainty, and supports more timely and accurate decision-making while preserving clinician judgment as central.

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