ViMDT: a clinical data visual analysis tool for multi-disciplinary treatment of lung cancer.

ABSTRACT: Multi-disciplinary treatment (MDT) has become a routine practice in clinical cancer diagnosis and treatment, playing an indispensable role in clinical decision-making. By integrating expertise from multiple disciplines, MDT provides patients with individualized diagnosis and treatment strategies. However, there is not yet a specialized clinical data visualization tool for MDT. This paper develops a novel clinical data analysis visualization tool for MDT, which analyzes in-depth and displays patient data comprehensively. Specifically, this tool designs a latent Dirichlet allocation (LDA)-based visualization model for clinical unstructured data, and Z-Score-3σ transformation and hierarchical strategies for clinical structural data. Moreover, we propose to predict personalized anti-tumor drug

SUBMITTER: Zhu W 

PROVIDER: S-EPMC12819497 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature