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    "story_id": "mp-2026-08-19-007",
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    "headline": "The Forecast Had to Cite Evidence for a Future Code",
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    "dek": "A bounded research workflow combined an EHR prior, medical search and code dictionaries before ranking next-encounter diagnoses.",
    "summary": "A bounded research workflow combined an EHR prior, medical search and code dictionaries before ranking next-encounter diagnoses.",
    "body_text": "ICD-Deepresearch predicts diagnosis codes that may appear at a future visit, where no source can reveal the answer in advance. It expands candidates from an EHR foundation model, adds a separate direct forecast, validates exact code semantics and writes rationales only after selection. Patient-averaged precision remained about 25 percent, while recall reached 35.09 percent on MIMIC-III and 48.32 percent on MIMIC-IV; physicians nevertheless rated its retrieved documents more useful than the standalone research comparisons.",
    "why_it_matters": "A bounded research workflow combined an EHR prior, medical search and code dictionaries before ranking next-encounter diagnoses.",
    "limitations": [
      "It expands candidates from an EHR foundation model, adds a separate direct forecast, validates exact code semantics and writes rationales only after selection."
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    "first_published_at": "2026-08-19T09:00:00.000-04:00",
    "modified_at": "2026-08-19T09:00:00.000-04:00",
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    "tags": [
      "EHR",
      "clinical forecasting",
      "agents",
      "evidence retrieval"
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  "sources": [
    {
      "source_id": "source-2026-08-19-007",
      "title": "arXiv preprint 2608.17075",
      "publisher": "arXiv",
      "url": "https://arxiv.org/abs/2608.17075",
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      "published_at": "2026-08-16T20:00:00.000-04:00",
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  "cite_this_report": {
    "title": "The Forecast Had to Cite Evidence for a Future Code",
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    "published_at": "2026-08-19T09:00:00.000-04:00",
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