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The burden of esophageal squamous cell carcinoma (ESCC) in China is substantial, with 85% of the cancers being in the progressive stage. The treatment for advanced ESCC are extremely limited, and immunotherapy, represented by PD-1 inhibitors, has demonstrated a promising application potential. However, the effectiveness of PD-1 inhibitors varies significantly among patients with different types of ESCC, and currently, there is no effective method to predict the response to PD-1 inhibitors. In this study, investigators aim to construct a multimodal deep learning-based model to predict the level of immune infiltration and the efficacy of immunotherapy for ESCC, integrating both pathological image features and clinical information of patients with ESCC, thereby enhancing the level of individualized and precise treatment for ESCC.
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110 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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