[
    {
        "id": "osp-16183",
        "type": "article-journal",
        "title": "ARISE: Adaptive Agentic Reasoning with Image-grounded Self-Evaluation for Interpretable IBD Assessment",
        "author": [
            {
                "family": "Banerjee",
                "given": "Pronoma"
            },
            {
                "family": "Shah",
                "given": "Anuva"
            },
            {
                "family": "Wu",
                "given": "Jason"
            },
            {
                "family": "Rahman",
                "given": "Md. Masudur"
            },
            {
                "family": "Mohanty",
                "given": "Sanjay"
            },
            {
                "family": "Kurada",
                "given": "Satya"
            },
            {
                "family": "Wachs",
                "given": "Juan P."
            }
        ],
        "URL": "https://omanscience.com/ar/articles/arise-adaptive-agentic-reasoning-with-image-grounded-self-evaluation-for-interpretable-ibd-assessment",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Inflammatory bowel disease (IBD) requires frequent imaging-based assessment, yet interpretation of modalities such as wireless capsule endoscopy (WCE) and intestinal ultrasound remains heavily dependent on specialist expertise. Vision-Language Models (VLMs) demonstrate significant potential in multimodal medical image analysis, but their clinical adoption is hindered by their insufficient domain-specific reasoning, susceptibility to hallucination, scarcity of high quality training data in fine-grained diagnostics and limited interpretability. We introduce ARISE (Adaptive Agentic Reasoning with Image-grounded Self-Evaluation), an autonomous planning framework that models few-shot medical image understanding as a sequential agentic workflow. ARISE structures agent execution into a transparent 5-stage workflow: hypothesis generation, image-grounded evidence summarization, evidence-conditioned refinement, symbolic verification, and final diagnosis. We apply ARISE to IBD assessment across two independent patient cohorts: wireless capsule endoscopy (WCE) images for Crohn's disease and B-mode ultrasound data for ulcerative colitis. ARISE consistently improves diagnostic performance over baseline VLMs while exposing where reasoning succeeds or fails, providing a more interpretable basis for clinical decision support and realistic deployment."
    }
]