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Efficient 18F-fluorodeoxyglucose positron emission tomography/computed tomography-based machine learning model for predicting epidermal growth factor receptor mutations in non-small cell lung cancer. 基于18F-氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描的高效机器学习模型,用于预测非小细胞肺癌的表皮生长因子受体突变。
4区 经济学 Q4 ECONOMICS Pub Date : 2024-03-01 Epub Date: 2022-04-14 DOI: 10.23736/S1824-4785.22.03441-0
Dan Ruan, Janyao Fang, Xinyu Teng

Background: Beyond the human eye's limitations, radiomics provides more information that can be used for diagnosis. We develop a personalized and efficient model based on 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) to predict epidermal growth factor receptor (EGFR) mutations to help identify which non-small cell cancer (NSCLC) patients are candidates for EGFR-tyrosine kinase inhibitors (TKIs) therapy.

Methods: We retrospectively included 100 patients with NSCLC and randomized them according to 70 patients in the training group and 30 patients in the validation group. The least absolute shrinkage and selection operator logistic regression (LLR) algorithm and support vector machine (SVM) classifier were used to build the models and predict whether EGFR is mutated or not. The predictive efficacy of the LLR algorithm-based model and the SVM classifier-based model was evaluated by plotting the receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC).

Results: The AUC, sensitivity and specificity of our radiomics model by LLR algorithm were 0.792, 0.967, and 0.600 for the training group and 0.643, 1.00, and 0.378 for the validation group, respectively, in predicting EGFR mutations. The AUC was 0.838 for the training group and 0.696 for the validation group after combining radiomics features with clinical features. The prediction results based on the SVM classifier showed that the validation group had the best performance when based on radial kernel function with AUC, sensitivity, and specificity of 0.741, 0.667, and 0.825, respectively.

Conclusions: Radiomics models based on 18F-FDG PET/CT modeled with different machine learning algorithms can improve the predictive efficacy of the models. Models that combine clinical features are more clinically valuable.

背景:除了人眼的局限性,放射组学提供了更多可用于诊断的信息。我们开发了一种基于18F-氟脱氧葡萄糖(18F-FDG)正电子发射断层扫描/计算机断层扫描(PET/CT)的个性化高效模型,用于预测表皮生长因子受体(EGFR)突变,帮助确定哪些非小细胞癌(NSCLC)患者适合接受EGFR-酪氨酸激酶抑制剂(TKIs)治疗:我们回顾性地纳入了100例NSCLC患者,并将他们随机分为70例训练组和30例验证组。采用最小绝对缩小和选择算子逻辑回归(LLR)算法和支持向量机(SVM)分类器建立模型,预测表皮生长因子受体(EGFR)是否突变。通过绘制接收者操作特征曲线(ROC)和计算曲线下面积(AUC),评估了基于LLR算法的模型和基于SVM分类器的模型的预测效果:在预测表皮生长因子受体(EGFR)突变方面,训练组的AUC、灵敏度和特异性分别为0.792、0.967和0.600,验证组的AUC、灵敏度和特异性分别为0.643、1.00和0.378。将放射组学特征与临床特征相结合后,训练组的 AUC 为 0.838,验证组为 0.696。基于 SVM 分类器的预测结果显示,验证组基于径向核函数的预测结果最好,AUC、灵敏度和特异性分别为 0.741、0.667 和 0.825:基于18F-FDG PET/CT的放射组学模型采用不同的机器学习算法建模,可以提高模型的预测效果。结合临床特征的模型更有临床价值。
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引用次数: 0
Comparison of Machine Learning Algorithms for Creation of a Bitcoin Price Prediction Model 创建比特币价格预测模型的机器学习算法比较
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-31 DOI: 10.18267/j.polek.1397
Milan Cibuľa, Michal Tkáč
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引用次数: 0
Užitečná kniha spojující teorii a praxi 一本理论与实践相结合的实用书籍
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-31 DOI: 10.18267/j.polek.1417
Eva Kislingerová, Tomáš Krabec
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引用次数: 0
Nositelé Nobelovy ceny za ekonomii pro rok 2021 2021 年诺贝尔经济学奖
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-23 DOI: 10.18267/j.polek.1354
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引用次数: 0
Salary Distribution and Percentages of Low-salary Workers in the Public Sector, Focusing on the First Year of the COVID-19 Pandemic 公共部门低收入工人的工资分布和百分比,重点是2019冠状病毒病大流行的第一年
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-11 DOI: 10.18267/j.polek.1403
Diana Bílková, Vlastimil Beran, Filip Červenka
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引用次数: 0
Economic Theory of Innovation 创新的经济理论
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-09 DOI: 10.18267/j.polek.1394
Marek Loužek
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引用次数: 0
Recovery of Claims Arising from Abuse of Non-insurance Social Security Benefit System 非保险社会保障福利制度滥用引起的索赔追偿
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-05 DOI: 10.18267/j.polek.1401
Gabriela Kukalová, Lukáš Moravec, Jana Hinke, Michaela Chladíková
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引用次数: 0
Kaldor-Hicks Improvement and Justice: To the Discussion on Normative Economics 卡尔多-希克斯改进与公正:对规范经济学的讨论
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-05 DOI: 10.18267/j.polek.1400
Lukáš Augustin Máslo
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引用次数: 0
Searching for Growth-conducive Institutions in Emerging Economies: A Stochastic Frontier Analysis 在新兴经济体中寻找有利于增长的制度:一个随机前沿分析
4区 经济学 Q4 ECONOMICS Pub Date : 2023-10-05 DOI: 10.18267/j.polek.1398
Woon Kan Yap, Jenny Gryzelius, Andrew Tek Wei Saw
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引用次数: 0
Determinants of Non-maturing Deposit Pass-through Rates in Eurozone Countries 欧元区国家未到期存款传递利率的决定因素
4区 经济学 Q4 ECONOMICS Pub Date : 2023-06-26 DOI: 10.18267/j.polek.1388
Milan Fičura, Jiří Witzany
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引用次数: 0
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Politicka Ekonomie
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