主动学习框架提高肿瘤变异解读准确性。
An Active Learning Framework Improves Tumor Variant Interpretation.
机构信息
Department of Biochemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee.
Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.
出版信息
Cancer Res. 2022 Aug 3;82(15):2704-2715. doi: 10.1158/0008-5472.CAN-21-3798.
Abstract
A novel machine learning approach predicts the impact of tumor mutations on cellular phenotypes, overcomes limited training data, minimizes costly functional validation, and advances efforts to implement cancer precision medicine.
摘要
一种新的机器学习方法可以预测肿瘤突变对细胞表型的影响，克服了有限的训练数据，最大限度地减少了昂贵的功能验证，并推进了实施癌症精准医学的努力。
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