{
  "abstract": "Assessing postoperative inflammation following trans-PRK and FS-LASIK remains challenging. This study proposes a multimodal fusion framework supported by inflammatory dynamics physical descriptors. The model uses modality-specific encoders for ocular imaging and structured clinical or biomarker sequences, uses explicit observation masks for unavailable modalities, and learns visit-level fusion weights using cross-modal attention modules. In the four de-identified retrospective data partitions evaluated in this study, the proposed fusion model increases the accuracy of the strongest baseline reported in each partition by 2.66 to 4.10% points, and shows similar improvements in F1 score and AUROC. The results indicate that intermediate multimodal fusion can support postoperative inflammation assessment. Before clinical deployment, larger external validation cohorts, calibration analyses, and direct comparisons with medical multimodal fusion methods are still required.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Ophthalmology, the First Affiliated Hospital of Henan Medical University",
    "Clinical Medical College, Shandong Second Medical University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Zeyu Yan"
    },
    {
      "affs": [
        0
      ],
      "name": "Yan Li"
    },
    {
      "affs": [
        1
      ],
      "name": "Fan Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Haibo Yan"
    },
    {
      "affs": [
        0
      ],
      "name": "Shiyang Niu"
    },
    {
      "affs": [
        0
      ],
      "name": "Hua Yang"
    },
    {
      "affs": [
        0
      ],
      "name": "Baojun Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6bvf0by9ttvgj.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-69257-0",
  "fulltext_url": "https://doi.org/10.1038/s41598-026-69257-0",
  "id": "6bvf0by9ttvgj",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://doi.org/10.1038/s41598-026-69257-0",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "Q"
    ],
    [
      "lcc",
      "R"
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      "openalex",
      "2741|Corneal surgery and disorders"
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  "openalex": "W7206190144",
  "pdf_url": "https://www.nature.com/articles/s41598-026-69257-0_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-01",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/6bvf0by9ttvgj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:45:53Z",
      "native_id": "62d62ca79ab4480584696f7265d90afb",
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      "url": "https://doi.org/10.1038/s41598-026-69257-0"
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  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2741|Corneal surgery and disorders",
      "subfield": "imaging"
    }
  ],
  "title": "Intelligent evaluation method for inflammatory response after trans-PRK and FS-LASIK based on multimodal feature fusion",
  "title_text": "Intelligent evaluation method for inflammatory response after trans-PRK and FS-LASIK based on multimodal feature fusion",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:45:53Z",
  "url": "https://research.draconitic.com/paper/6bvf0by9ttvgj",
  "venue": "Scientific Reports",
  "versions": []
}