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This study is based on the Nicheng Cohort study. This study intends to analyze whether AI assistance can effectively improve the efficiency and accuracy of quality control of data collected in large-scale epidemiological surveys based on traditional quality control processes.
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This study randomly divided quality control personnel into an experimental group and a control group. The experimental group adopts AI assisted quality control: the AI system automatically transcribes the recorded text of the questionnaire, extracts keywords, analyzes the consistency of the Q&A logic, and generates quality control prompts. The quality control personnel will verify the question fragments according to the prompts and determine the qualification of the questionnaire; The control group relies entirely on manual quality control: the quality control personnel listen to the recording word by word, manually record the content, independently identify keyword omissions, logical contradictions, or terminology deviations, and ultimately determine whether the questionnaire is qualified. The core difference lies in the fact that the experimental group uses AI technology to accurately locate risk issues, reducing the burden of manual comprehensive screening, while the control group requires full manual review without targeted support.
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900 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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