{
  "abstract": "Background: Small bowel capsule endoscopy (SBCE) is widely used to evaluate small bowel involvement in Crohn disease (CD); however, manual Lewis score calculation is time-consuming and susceptible to interobserver variability.\n\nObjective: This study aimed to develop and preliminarily validate a multitask deep learning system for automated Lewis score estimation in patients with small bowel CD undergoing SBCE.\n\nMethods: We developed Eval-Model, a multitask framework integrating You Only Look Once (YOLO)–style lesion detection and localization for ulcers and edema, a stenosis classification branch, and a long short-term memory–based temporal regression module. The primary dataset comprised SBCE examinations from 814 patients at the Children’s Hospital of Fudan University. In this dataset, 725 (89.1%) cases were included for lesion-level annotation, and 89 (10.9%) cases with expert-consensus Lewis scores were used for scoring model development and internal testing. These 89 cases comprised 49 (55.1%) training cases and 40 (44.9%) internal test cases. All splits were performed at the patient level. A retrospective same-center temporal validation cohort of 20 consecutive cases from 2026 and 5 control cases were used for preliminary assessments of temporal robustness and specificity.\n\nResults: In the 40-case internal Lewis score test set, Eval-Model achieved a mean squared error of 14.693 (95% CI 8.72-22.15), root mean squared error of 3.833 (95% CI 2.95-4.71), mean absolute error of 2.9 (95% CI 2.1-3.8), R2 of 0.82 (95% CI 0.70-0.90), and explained variance of 0.83 (95% CI 0.72-0.91). For lesion recognition, the model achieved an overall mean average precision of 0.94 with an inference time of 15 ms per frame. In the 20-case same-center temporal validation cohort, the mean squared error was 26.848 (95% CI 12.51-45.33), the root mean squared error was 5.182 (95% CI 3.54-6.73), the mean absolute error was 3.3 (95% CI 2.2-4.6), R2 rounded to 1.00 (95% CI 0.98-1.00), and the explained variance rounded to 1.00 (95% CI 0.98-1.00). These temporal estimates require cautious interpretation because of the small, same-center cohort.\n\nConclusions: Eval-Model demonstrated preliminary feasibility for automated Lewis score estimation from SBCE in small bowel CD. The system may serve as a standardized adjunct to expert review, but larger multicenter prospective validation with independent external annotation is required before clinical deployment.",
  "abstract_shown": true,
  "affiliations": [
    "Children's Hospital of Fudan University Shanghai China",
    "Chongqing Jinshan Technology (Group) Co, Ltd Chongqing China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yingying Meng",
      "orcid": "0000-0002-9542-7933"
    },
    {
      "affs": [
        1
      ],
      "name": "Min Gao",
      "orcid": "0000-0002-4969-2488"
    },
    {
      "affs": [
        0
      ],
      "name": "Jie Wu",
      "orcid": "0000-0002-6831-3981"
    },
    {
      "affs": [
        0
      ],
      "name": "Ying Huang",
      "orcid": "0000-0002-4931-4006"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4qg3wvhh6s3vs.bib",
  "cited_by": 0,
  "doi": "10.2196/92416",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13714523/",
  "id": "4qg3wvhh6s3vs",
  "issns": [
    "2291-9694"
  ],
  "landing_url": "https://doi.org/10.2196/92416",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "Original Paper"
    ],
    [
      "openalex",
      "1311|Inflammatory Bowel Disease"
    ]
  ],
  "openalex": "W7130652725",
  "pdf_url": null,
  "pmcid": "PMC13714523",
  "pmid": "42867883",
  "published": "2026-10-13",
  "publisher": "JMIR Publications Inc.",
  "ris": "https://research.draconitic.com/paper/4qg3wvhh6s3vs.ris",
  "sources": [
    {
      "first_seen": "2026-11-01T12:22:00Z",
      "native_id": "PMC13714523",
      "source": "pmc",
      "url": "https://doi.org/10.2196/92416"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:1311|Inflammatory Bowel Disease",
      "subfield": "genetics-genomics"
    }
  ],
  "title": "Automated Lewis Score Estimation for Small Bowel Crohn Disease Using Capsule Endoscopy: Retrospective Cohort Study",
  "title_text": "Automated Lewis Score Estimation for Small Bowel Crohn Disease Using Capsule Endoscopy: Retrospective Cohort Study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T12:22:00Z",
  "url": "https://research.draconitic.com/paper/4qg3wvhh6s3vs",
  "venue": "JMIR Medical Informatics",
  "versions": []
}