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Machine Learning-Assisted System for Thyroid Nodule Diagnosis

文献类型：期刊论文

作者Zhang, Bin1; Tian, Jie3; Pei, Shufang4; Chen, Yubing2; He, Xin6; Dong, Yuhao5; Zhang, Lu5; Mo, Xiaokai5; Huang, Wenhui5; Cong, Shuzhen4
刊名THYROID
出版日期2019-04-27
页码10
关键词thyroid nodule ultrasound machine learning random forest diagnosis
ISSN号1050-7256
DOI10.1089/thy.2018.0380
通讯作者Zhang, Shuixing(shui7515@126.com)
英文摘要Background: Ultrasound (US) examination is helpful in the differential diagnosis of thyroid nodules (malignant vs. benign), but its accuracy relies heavily on examiner experience. Therefore, the aim of this study was to develop a less subjective diagnostic model aided by machine learning. Methods: A total of 2064 thyroid nodules (2032 patients, 695 male; M-age = 45.25 +/- 13.49 years) met all of the following inclusion criteria: (i) hemi- or total thyroidectomy, (ii) maximum nodule diameter 2.5 cm, (iii) examination by conventional US and real-time elastography within one month before surgery, and (iv) no previous thyroid surgery or percutaneous thermotherapy. Models were developed using 60% of randomly selected samples based on nine commonly used algorithms, and validated using the remaining 40% of cases. All models function with a validation data set that has a pretest probability of malignancy of 10%. The models were refined with machine learning that consisted of 1000 repetitions of derivatization and validation, and compared to diagnosis by an experienced radiologist. Sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated. Results: A random forest algorithm led to the best diagnostic model, which performed better than radiologist diagnosis based on conventional US only (AUC = 0.924 [confidence interval (CI) 0.895-0.953] vs. 0.834 [CI 0.815-0.853]) and based on both conventional US and real-time elastography (AUC = 0.938 [CI 0.914-0.961] vs. 0.843 [CI 0.829-0.857]). Conclusions: Machine-learning algorithms based on US examinations, particularly the random forest classifier, may diagnose malignant thyroid nodules better than radiologists.
WOS关键词SHEAR-WAVE ELASTOGRAPHY ; FINE-NEEDLE-ASPIRATION ; REAL-TIME ELASTOGRAPHY ; DIFFERENTIAL-DIAGNOSIS ; ULTRASOUND ELASTOGRAPHY ; MANAGEMENT ; BENIGN ; US ; PERFORMANCE ; ACCURACY
资助项目National Scientific Foundation of China[81571664] ; National Scientific Foundation of China[81871323] ; National Scientific Foundation of China[81801665] ; Science and Technology Planning Project of Guangdong Province[2014A020212244] ; Science and Technology Planning Project of Guangdong Province[2016A020216020] ; Scientific Research General Project of Guangzhou Science Technology and Innovation Commission[201605110912158] ; China Postdoctoral Science Foundation[2016M600145] ; Guangdong Grand Science and Technology Special Project[2015B010106008]
WOS研究方向Endocrinology & Metabolism
语种英语
WOS记录号WOS:000466533800001
出版者MARY ANN LIEBERT, INC
资助机构National Scientific Foundation of China ; Science and Technology Planning Project of Guangdong Province ; Scientific Research General Project of Guangzhou Science Technology and Innovation Commission ; China Postdoctoral Science Foundation ; Guangdong Grand Science and Technology Special Project
源URL[http://ir.ia.ac.cn/handle/173211/24908]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Zhang, Shuixing
作者单位1.Jinan Univ, Affiliated Hosp 1, Dept Radiol, Guangzhou, Guangdong, Peoples R China
2.Jinan Univ, Affiliated Hosp 1, Informat Ctr, Guangzhou, Guangdong, Peoples R China
3.Chinese Acad Sci, Key Lab Mol Imaging, Beijing, Peoples R China
4.Acad Med Sci, Guangdong Prov Peoples Hosp, Dept Ultrasound, Guangzhou, Guangdong, Peoples R China
5.Acad Med Sci, Guangdong Prov Peoples Hosp, Dept Radiol, Guangzhou, Guangdong, Peoples R China
6.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Bin,Tian, Jie,Pei, Shufang,et al. Machine Learning-Assisted System for Thyroid Nodule Diagnosis[J]. THYROID,2019:10.
APA Zhang, Bin.,Tian, Jie.,Pei, Shufang.,Chen, Yubing.,He, Xin.,...&Zhang, Shuixing.(2019).Machine Learning-Assisted System for Thyroid Nodule Diagnosis.THYROID,10.
MLA Zhang, Bin,et al."Machine Learning-Assisted System for Thyroid Nodule Diagnosis".THYROID (2019):10.

入库方式： OAI收割

来源：自动化研究所

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