| Autor: |
Yanwei Zhang, Beibei Sun, Yinghong Yu, Jun Lu, Yuqing Lou, Fangfei Qian, Tianxiang Chen, Li Zhang, Jiancheng Yang, Hua Zhong, Ligang Wu, Baohui Han |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
npj Precision Oncology, Vol 8, Iss 1, Pp 1-6 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2397-768X |
| DOI: |
10.1038/s41698-024-00551-8 |
| Popis: |
Abstract This research explores the potential of multimodal fusion for the differential diagnosis of early-stage lung adenocarcinoma (LUAD) (tumor sizes < 2 cm). It combines liquid biopsy biomarkers, specifically extracellular vesicle long RNA (evlRNA) and the computed tomography (CT) attributes. The fusion model achieves an impressive area under receiver operating characteristic curve (AUC) of 91.9% for the four-classification of adenocarcinoma, along with a benign-malignant AUC of 94.8% (sensitivity: 89.1%, specificity: 94.3%). These outcomes outperform the diagnostic capabilities of the single-modal models and human experts. A comprehensive SHapley Additive exPlanations (SHAP) is provided to offer deep insights into model predictions. Our findings reveal the complementary interplay between evlRNA and image-based characteristics, underscoring the significance of integrating diverse modalities in diagnosing early-stage LUAD. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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