کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11002747 | 1447919 | 2018 | 34 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Boosting support vector machines for cancer discrimination tasks
ترجمه فارسی عنوان
تقویت دستگاه های بردار پشتیبانی برای وظایف تشخیص سرطان
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کلمات کلیدی
فراگیری ماشین، ژنومیک سرطان، طبقه بندی سرطان، شناسایی سرطان، درمان شخصی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Cancer is a complex disease that is caused by rapid alteration of genes. Prediction of the state of cancer in advance contributes to a better understanding of its mechanism and improves the cancer therapy process. For example, predicting the malignancy of tumors in advance can prevent the development of cancer through the early treatment and clinical management of tumor progression. Despite generation of extensive clinical data obtained from the high-throughput technologies, it is necessary to develop machine learning algorithms to guide the prediction process. In the study, we utilize boosting and develop three computational methods to increase the performance of support vector machines (SVM). The aforementioned methods improve the performance over existing state-of-the-art algorithms, including SVM and xgboost. We evaluate the proposed boosting approach relative to the existing algorithms by using several gene expression data related to oral cancer, breast cancer, pheochromocytomas and paragangliomas, bladder cancer, and gastric cancer. The reported results using several performance measures indicate that algorithms employing the proposed approach outperform algorithms employing the baseline approach.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 101, 1 October 2018, Pages 236-249
Journal: Computers in Biology and Medicine - Volume 101, 1 October 2018, Pages 236-249
نویسندگان
Turki Turki, Zhi Wei,