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    <identifier>10.57760/sciencedb.j00133.00590</identifier>
    <datestamp>2025-12-05T16:25:37Z</datestamp>
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  <dc:date>2025-12-05</dc:date>
  <dc:title>Diabetes Question-Answering Model Evaluation Test Set</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.j00133.00590</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>This test set was curated through a systematic selection process based on the CMtMedQA dataset (https://huggingface.co/datasets/Suprit/CMtMedQA). CMtMedQA, provided by Suprit, contains approximately 70,000 authentic multi-turn doctor&amp;ndash;patient dialogues across 14 clinical departments and is widely used as a foundational resource in Chinese medical dialogue research.To construct the present test set, candidate samples were first retrieved from the original CMtMedQA dialogues using domain-specific keywords such as &amp;ldquo;diabetes,&amp;rdquo; &amp;ldquo;endocrinology,&amp;rdquo; and &amp;ldquo;blood glucose,&amp;rdquo; yielding a subset relevant to chronic disease scenarios. Subsequently, in accordance with the requirements of multi-turn interaction, only dialogues in which the patient contributed more than three turns were retained. All candidate dialogues underwent case-by-case verification by clinical experts, who reviewed the medical topics, content completeness, and linguistic accuracy. After this expert validation process, a total of 100 authentic multi-turn patient dialogues were selected to form the released test set, providing data support for question-answering tasks related to chronic disease management.</dc:description>
  <dc:subject>Diabetes; multi-turn medical dialogue; doctor–patient question answering; chronic disease management</dc:subject>
  <dc:creator>ma ya kun</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
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  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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