[
    {
        "id": "osp-15342",
        "type": "article-journal",
        "title": "Dual- versus Single-Suggestion AI Support for Radiographic Interpretation in Residents: Randomized Multireader Study",
        "author": [
            {
                "family": "Wu",
                "given": "Lin"
            },
            {
                "family": "Xu",
                "given": "Zhe"
            },
            {
                "family": "Wang",
                "given": "Hongyi"
            },
            {
                "family": "Zhou",
                "given": "Feifei"
            },
            {
                "family": "Deng",
                "given": "Wei"
            },
            {
                "family": "Zhang",
                "given": "Chunlong"
            },
            {
                "family": "Zhu",
                "given": "Yuting"
            },
            {
                "family": "Chen",
                "given": "Kaixiao"
            },
            {
                "family": "Liang",
                "given": "Xiao"
            },
            {
                "family": "Yang",
                "given": "Chen"
            },
            {
                "family": "Chen",
                "given": "Yeyuan"
            },
            {
                "family": "Chen",
                "given": "Hao"
            },
            {
                "family": "Zhou",
                "given": "Fuqing"
            }
        ],
        "URL": "https://omanscience.com/en/articles/dual-versus-single-suggestion-ai-support-for-radiographic-interpretation-in-residents-randomized-multireader-study",
        "language": "en",
        "issued": {
            "date-parts": [
                [
                    2026
                ]
            ]
        },
        "abstract": "Purpose: To compare dual- and single-suggestion AI support for radiographic interpretation by residents, particularly when the shared AI suggestion was incorrect. Materials and Methods: This prospective, multicenter, randomized three-arm reader study was conducted at three hospitals in China from July to September 2026 (ChiCTR2600129243). After specialty stratification, 132 residents with fewer than 3 years of clinical experience were randomized 1:1:1 to GPT-5.4 alone (group A), GPT-5.4 plus Kimi-K2.6 (group B), or GPT-5.4 plus Gemini-3.6 Flash (group C); 123 were analyzed. Participants interpreted 60 radiographs before and after AI support. The primary outcome was accuracy change. Welch ANOVA and Holm-adjusted t tests compared support conditions; HC3 linear models assessed specialty interaction. Results: Among 123 residents (mean age, 24.1 years +/- 1.4; 65 women), radiology residents showed greater accuracy improvement with dual- than single-suggestion support (B-A, 6.69 percentage points [95% CI, 0.97-12.40]; C-A, 7.87 percentage points [95% CI, 1.64-14.11]; Holm-adjusted P = .030 for both), whereas accuracy change did not differ in non-radiology residents (P = .20). When GPT-5.4 was incorrect, AI-assisted accuracy was higher with dual- than single-suggestion support in radiology residents (40.1% and 40.4% vs 20.0%) and non-radiology residents (31.3% and 31.0% vs 12.1%) (all Holm-adjusted P < .001). The dual-suggestion effect differed by specialty (interaction difference, 10.44 percentage points; 95% CI, 4.36-16.52; P < .001). Conclusion: Dual-suggestion support may mitigate the influence of erroneous AI suggestions, with greater accuracy improvement observed in radiology but not non-radiology residents."
    }
]