Titlebook: Machine and Deep Learning in Oncology, Medical Physics and Radiology; Issam El Naqa,Martin J. Murphy Book 2022Latest edition Springer Natu

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書目名稱Machine and Deep Learning in Oncology, Medical Physics and Radiology影響因子(影響力)




書目名稱Machine and Deep Learning in Oncology, Medical Physics and Radiology影響因子(影響力)學(xué)科排名




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書目名稱Machine and Deep Learning in Oncology, Medical Physics and Radiology網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Machine and Deep Learning in Oncology, Medical Physics and Radiology被引頻次




書目名稱Machine and Deep Learning in Oncology, Medical Physics and Radiology被引頻次學(xué)科排名




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Conventional Machine Learning Methodse principal component analysis and clustering (unsupervised), logistic regression, neural network, support vector machine, decision tree, Bayesian networks, and naive Bayes (supervised) in addition to reinforcement learning.

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Performance Evaluationof that test. The purpose of this chapter is to review these techniques in so far as they apply to advances in Oncology, Medical Physics, and Radiology and to discuss additional evaluation techniques particularly suited for these tasks.

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