Comparative analysis of AI algorithms on real medical data for chronic pain detection

Abstract

Our findings demonstrate the effectiveness of AI in identifying chronic pain cases from fragmentary clinical notes. By focusing on concise, keyword-oriented text, this work establishes a solid baseline for domain-specific NLP approaches in healthcare. The proposed method reduces the burden of manual review, facilitates real-time decision support, and may standardize chronic pain assessment processes. Furthermore, we plan to explore new embedding techniques specifically designed for short, context-limited clinical notes, where dynamic contextual models (e.g., BERT) often encounter challenges due to insufficient extended textual context.

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