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Updated: Jan 20, 2026

Leveraging CyVerse Resources for De Novo Comparative Transcriptomics of Underserved Non-model Organisms
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利用机器学习来预测肺移植后的皮肤恶性瘤

Nasim Nosoudi1, Amir Zadeh2, Rayna Nichols3

  • 1Department of Biomedical Engineering and Human Factor, College of Engineering, Wright State University, Dayton, OH, USA.

Lung cancer management
|January 19, 2026
PubMed
概括

机器学习模型预测了肺移植接受者的移植后恶性瘤风险. 关键预测因素包括HLA-DR等位基因,BMI和CMV/EBV血清状况,使个性化风险评估成为可能.

关键词:
一个新的恶性瘤.在 HLA-DR 组合下,肺移植 肺移植 肺移植机器学习是机器学习.预测建模预测建模皮肤癌是皮肤癌.

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