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LLMs and templates offer trade-offs for AI clinical report generation

A new paper compares a rule-based template system with GPT-4 for generating clinical reports in remote cognitive remediation settings. The study found that while the template system offered greater clinical reliability and traceability, GPT-4 produced more concise outputs. Both approaches used identical structured variables, and evaluations by speech therapists highlighted a trade-off between reliability and linguistic quality, leading to design recommendations for future systems. AI

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IMPACT Illustrates a trade-off between AI's conciseness and template systems' reliability in specialized clinical reporting.

RANK_REASON The cluster contains an academic paper detailing a comparison of AI and template-based systems for a specific application.

Read on arXiv cs.CL →

COVERAGE [2]

  1. arXiv cs.CL TIER_1 · Yongxin Zhou, Fabien Ringeval, Fran\c{c}ois Portet ·

    Automated Clinical Report Generation for Remote Cognitive Remediation: Comparing Knowledge-Engineered Templates and LLMs in Low-Resource Settings

    arXiv:2605.06594v1 Announce Type: new Abstract: The growing demand for cognitive remediation therapy, combined with limited speech therapist availability, has accelerated the adoption of remote rehabilitation tools. These systems generate large volumes of interaction data that ar…

  2. arXiv cs.CL TIER_1 · François Portet ·

    Automated Clinical Report Generation for Remote Cognitive Remediation: Comparing Knowledge-Engineered Templates and LLMs in Low-Resource Settings

    The growing demand for cognitive remediation therapy, combined with limited speech therapist availability, has accelerated the adoption of remote rehabilitation tools. These systems generate large volumes of interaction data that are difficult for clinicians to review efficiently…