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Comparison of machine learning models for the prediction of cancer cells using MHC class I complexes

机译:使用MHC级联癌细胞预测机器学习模型的比较

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Currently, cancer is the leading cause of death worldwide, making millions of deaths annually in developing countries due to a shortage of detection and treatment. Early detection of cancer neoantigens is useful for specialists because they can help in the development of more successful treatments. Based on this problem, the objective of this work is to carry out a comparative process between machine learning models, to determine which of them allows an adequate prediction of the data, and thus determine the carcinogenic neoantigens. For this, information extracted from protein sequences was employed. The preliminary results show sensitivity and specificity of 1.0 and 0.98 respectively.
机译:目前,癌症是全世界死亡的主要原因,由于缺乏检测和治疗,发展中国家每年都在数百万死亡。早期发现癌症新奥地利人对专家有用,因为它们可以帮助发展更成功的治疗方法。在此问题的基础上,这项工作的目的是在机器学习模型之间进行比较过程,以确定它们中的哪一个允许足够的数据预测,从而确定致癌新奥地利古代。为此,采用从蛋白质序列中提取的信息。初步结果分别显示了1.0和0.98的敏感性和特异性。

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