[1] Jordan MI, Mitchell TM. Machine learning: Trends, perspectives, and prospects[J]. Science, 2015, 349(6245):255-260. [2] Lecun Y, Bengio Y, Hinton G. Deep learning[J]. Nature, 2015, 521(7553):436-444. [3] 张远望. 人工智能与应用 [J]. 中国科技纵横, 2015, (20):22 [4] 尼克·波斯特洛姆. 张体伟, 张玉青, 译.超级智能: 路线图、危险性与应对策略 [M].北京: 中信出版社, 2015. [5] Wang S, Summers RM. Machine learning and radiology[J]. Medical Image Analysis, 2012, 16(5):933-951. [6] Kooi T, Litjens G, Van Ginneken B, et al. Large scale deep learning for computer aided detection of mammographic lesions[J]. Med Image Anal, 2017, 35:303-312. [7] Holder LB, Haque MM, Skinner MK. Machine learning for epigenetics and future medical applications[J]. Epigenetics, 2017, 12(7):505-514. [8] Bakkar N, Kovalik T, Lorenzini I, et al. Artificial intelligence in neurodegenerative disease research: use of IBM Watson to identify additional RNA-binding proteins altered in amyotrophic lateral sclerosis[J]. Acta Neuropathologica, 2018, 135(2):227-247. [9] Kim SY, Diggans J, Pankratz D, et al. Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data.[J]. Lancet Respir Med, 2015, 3(6):473-482. [10] Choi H, Jin KH. Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging[J]. Behav Brain Res, 2018, 344:103-109. [11] Lu G, Little JV, Wang X, et al. Detection of head and neck cancer in surgical specimens using quantitative hyperspectral imaging[J]. Clin Cancer Res, 2017, 23(18):5426-5436. [12] Jeyaraj PR, Samuel Nadar ER.Computer-assisted medical image classifcation for early diagnosis of oral cancer employing deep learning algorithm[J]. J Cancer Res Clin Oncol, 2019, 145(4):829-837. [13] Halicek M, Little JV, Wang X, et al. Tumor margin classification of head and neck cancer using hyperspectral imaging and convolutional neural networks[J]. Proc SPIE Int Soc Opt Eng, 2018,10576:1057605. [14] Halicek M, Little JV, Wang X,et al.Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks[J]. J Biomed Opt, 2019, 24(3):1-9. [15] Uthoff RD, Song B, Sunny S, et al. Point-of-care, smartphone-based, dualmodality, dual-view, oral cancer screening device with neural network classification for low-resource communities[J]. PLoS One, 2018, 13(12):e0207493. [16] Kearney V, Chan JW, Valdes G, et al. The application of artificial intelligence in the IMRT planning process for head and neck cancer[J]. Oral Oncol, 2018, 87:111-116. [17] Ibragimov B, Xing L. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks[J]. Medical Physics, 2017, 44(2):547-557. [18] Ariji Y, Fukuda M, Kise Y, et al. Contrast-enhanced CT image assessment of cervical lymph node metastasis in oral cancer patients using a deep learning system of artificial intelligence[J]. Oral Surgery Oral Medicine Oral Pathology and Oral Radiology, 2019, 127(5):458-463. [19] Bur AM, Holcomb A, Goodwin S, et al. Machine learning to predict occult nodal metastasis in early oral squamous cell carcinoma[J]. Oral Oncol, 2019, 92:20-25. [20] Kann BH, Aneja S, Loganadane GV, et al. Pretreatment identification of head and neck cancer nodal metastasis and extranodal extension using deep learning neural networks[J]. Sci Rep, 2018, 8(1):14036. [21] Hiraiwa T, Ariji Y, Fukuda M, et al. A deep-learning artifcial intelligence system for assessment of root morphology of the mandibular frst molar on panoramic radiography[J]. Dentomaxillofac Radiol, 2019, 48(3):20180218. [22] Patil S, Kulkarni V, Bhise A. Algorithmic analysis for dental caries detection using an adaptive neural network architecture[J]. Heliyon, 2019, 5(5):e01579. [23] Zanella-Calzada LA, Galván-Tejada CE, Chávez-Lamas NM, et al. Deep artificial neural networks for the diagnostic of caries using socioeconomic and nutritional features as determinants: data from NHANES 2013-2014[J]. Bioengineering (Basel), 2018, 5(2):47. [24] Lee JH, Kim DH, Jeong SN, et al. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm[J]. J Dent, 2018, 77:106-111. [25] Aubreville M, Knipfer C, Oetter N, et al. Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning[J]. Sci Rep, 2017, 7(1):11979. [26] Ma L, Lu G, Wang D, et al. Deep learning based classification for head and neck cancer detection with hyperspectraln imaging in an animal model[J]. Proc SPIE Int Soc Opt Eng, 2017, 10137:101372G. [27] Halicek M, Lu G, Little JV, et al. Deep convolutional neural networks for classifying head and neck cancer using hyperspectral imaging[J]. J Biomed Opt, 2017, 22(6):60503. [28] Lee JH, Kim DH, Jeong SN, et al. Diagnosis and prediction of periodontally compromised teeth using a deep learning-based convolutional neural network algorithm[J]. J Periodontal Implant Sci, 2018, 48(2):114-123. |