Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma

Схожие документы

• Machine learning-derived identification of tumor-infiltrating immune cell-related signature for improving prognosis and immunotherapy responses in patients with skin cutaneous melanoma
  по: Shaolong Leng, и др.
  Опубликовано: (2023-09-01)
• Unveiling the link between inflammasomes and skin cutaneous melanoma: Insights into expression patterns and immunotherapy response prediction
  по: Yu Sheng, и др.
  Опубликовано: (2023-11-01)
• Research on the influence of radiotherapy-related genes on immune infiltration, immunotherapy response and prognosis in melanoma based on multi-omics
  по: Yujing Shi, и др.
  Опубликовано: (2024-12-01)
• Construction of immunotherapy-related prognostic gene signature and small molecule drug prediction for cutaneous melanoma
  по: Jiahua Xing, и др.
  Опубликовано: (2022-07-01)
• Core immune cell infiltration signatures identify molecular subtypes and promote precise checkpoint immunotherapy in cutaneous melanoma
  по: Zheng Zhu, и др.
  Опубликовано: (2022-08-01)