以上参考为为项目书中行业内评价论文列表中的论文：

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[2] Lussier F, Thibault V, Masson JF*, et al. Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering[J]. TrAC Trends in Analytical Chemistry, 2020, 124: 115796

[3] Zhan Q, Li Y, Yuan YH, et al. The accuracy of Raman spectroscopy in the detection and diagnosis of oral cancer: A systematic review and meta-analysis[J]. Journal of Raman Spectroscopy, 2020, 51(12): 2377-2397

[4] Alabi RO, Youssef O, Pirinen M, Elmusrati M, Mäkitie AA*, et al. Machine learning in oral squamous cell carcinoma: Current status, clinical concerns and prospects for future – A systematic review [J]. Artificial Intelligence in Medicine, 2021, 115: 1-14.

[5] Brouwer de Koning SG, Schaeffers AWMA, Schats W, van den Brekel MWM*, et al. Assessment of the deep resection margin during oral cancer surgery: A systematic review [J]. European Journal of Surgical Oncology, 2021, 47(9): 2220-2232.

[6] Blake N, Gaifulina R, Griffin LD, Bell IM, Thomas GMH*. Machine learning of Raman Spectroscopy Data for Classifying Cancers: A Review of the Recent [J]. Diagnostics, 2022, 12(6): 1491.

[7] Lin Y-Y, Tang M-M, Liu Y, Jiang M-J, He S-S, et al. A narrative review on machine learning in diagnosis and prognosis prediction for tongue squamous cell carcinoma [J]. Transactional Cancer Research, 2022, 11(12): 4409-4415.

[8] Elmakaty I, Elmarasi M, Amarah A, Abdo R, Malki MI*. Accuracy of artificial intelligence-assisted detection of Oral Squamous Cell Carcinoma: A systematic review and meta-analysis [J]. Critical Reviews in Oncology/Hematology, 2022, 178: 103777.

[9] López-Cortés XA, Matamala F, Venegas B, Rivera C. Machine-Learning Applications in Oral Cancer: A Systematic Review. Applied Sciences, 2022, 12(11): 5715.

[10] Alabi RO, Almangush A, Elmusrati M, Mäkitie AA*. Deep Machine for Oral Cancer: From Precise Diagnosis to Precision Medicine [J]. Frontiers in Oral Health, 2022, 2: 794248.