Multi-manufacturer drug identification based on near infrared spectroscopy and deep transfer learning

Lingqiao Li; Xipeng Pan; Wenli Chen; Manman Wei; Yanchun Feng; Lihui Yin; Changqin Hu; Huihua Yang

doi:10.1142/s1793545820500169

[1] H. Ma, J. Wang, Y. Chen, J. Cheng, Z. Lai et al., "Rapid authentication of starch adulterations in ultrafine granular powder of shanyao by near-infrared spectroscopy coupled with chemometric methods," Food Chem. 215, 108–115 (2017).

[2] L. M. M. Le, L. Eveleigh, I. Hasnaoui, P. Prognon, A. Baillet-Guffroy, E. Caudron, "Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin," J. Pharm. Biomed. Anal. 138, 249–255 (2017).

[3] J. Xue, L. Ye, C. Li, M. Zhang, P. Li, "Rapid and nondestructive measurement of glucose in a skin tissue phantom by near-infrared spectroscopy," Optik 170, 30–36 (2018).

[4] X. Chu, W. Lu, "Research and application progress of near infrared spectroscopy analytical technology in china in the past five years," Guang Pu Xue Yu 34(10), 2595–2605 (2014).

[5] R. Risoluti, S. Materazzi, A. Gregori, L. Ripani, "Early detection of emerging street drugs by near infrared spectroscopy and chemometrics," Talanta 153, 407–413 (2016).

[6] W. Zheng, L. Li, J. Hu, Y. Feng, L. Yin, C. Hu, H. Yang, "Drug discrimination by near infrared spectroscopy based on stacked sparse auto-encoders combined with kernel extreme learning machine," Chin. J. Anal. Chem. 46(9), 1446–1454 (2018).

[7] H. Yang, B. Hu, X. Pan, S. Yan, Y. Feng, X. Zhang, L. Yin, C. Hu, "Deep belief network-based drug identification using near infrared spectroscopy," J. Innov. Opt. Health Sci. 10(02), 1630011 (2017).

[8] Y. LeCun, Y. Bengio, G. Hinton, "Deep learning," Nature 521(7553), 436–444 (2015).

[9] L. Li, X. Pan, H. Yang, Z. Liu, Y. He, Z. Li, Y. Fan, Z. Cao, L. Zhang, "Multi-task deep learning for finegrained classification and grading in breast cancer histopathological images," Multimed. Tools Appl. 1–20 (2018). DOI: 10.1007/s11042-018-6970-9.

[10] C. Wang, X. Wu, L. Li, Y. Wang, Z. Li, "Convolutional Neural Network Application in Prediction of Soil Moisture Content," Spectrosc. Spect. Anal. 38(1), 36–41 (2018).

[11] M. Lu, K. Yang, P. Song, R. Shu, L. Wang, Y. Yang, H. Liu, J. Li, L. Zhao, Y. Zhang, "The study of classification modeling method for near infrared spectroscopy of tobacco leaves based on convolution neural network," Spectrosc. Spect. Anal. 38(12), 3724–3728 (2018).

[12] J. Acquarelli, T. van Laarhoven, J. Gerretzen, T. N. Tran, L. M. Buydens, E. Marchiori, "Convolutional neural networks for vibrational spectroscopic data analysis," Anal. Chim. Acta 954, 22–31 (2017).

[13] S. Pan, Q. Yang, "A survey on transfer learning," IEEE Trans. Knowl. Data Eng. 22(10), 1345–1359 (2009).

[14] J. Wang, Y. Chen, L. Hu, X. Peng, P. S. Yu. Stratified transfer learning for cross-domain activity recognition, in 2018 IEEE Int. Conf. Pervasive Computing and Communications (PerCom) (IEEE, 2018), pp. 1–10.

[15] D. S. Kermany, M. Goldbaum, W. Cai, C. C. Valentim, H. Liang, S. L. Baxter, A. McKeown, G. Yang, X. Wu, F. Yan et al., "Identifying medical diagnoses and treatable diseases by image-based deep learning," Cell 172(5), 1122–1131 (2018).

[16] J. Zhang, W. Li, P. Ogunbona, Joint geometrical and statistical alignment for visual domain adaptation, in Proc. IEEE Conf. Computer Vision and Pattern Recognition (2017), pp. 1859–1867.

[17] M. Long, J. Wang, Y. Cao, J. Sun, S. Y. Philip, "Deep learning of transferable representation for scalable domain adaptation," IEEE Trans. Knowl. Data Eng. 28(8), 2027–2040 (2016).

[18] M. Long, H. Zhu, J. Wang, M. I. Jordan. "Deep transfer learning with joint adaptation networks," in Proc. 34th Int. Conf. Machine Learning, Vol. 70 (JMLR.org, 2017), pp. 2208–2217.

[19] X. Zhang, T. Lin, J. Xu, X. Luo, Y. Ying, "Deepspectra: An end-to-end deep learning approach for quantitative spectral analysis," Anal. Chim. Acta 1058, 48–57 (2019).

[20] B. T. Le, D. Xiao, Y. Mao, D. He, "Coal analysis based on visible-infrared spectroscopy and a deep neural network," Infr. Phys. Technol. 93, 34–40 (2018).

[21] L. Li, X. Pan, H. Yang, Z. Liu, Y. He, Z. Li, Y. Fan, Z. Cao, L. Zhang, "Deep convolution network application in identication of multi-variety and multimanufacturer pharmaceutical," Spectrosc. Spect. Anal. 39(11), 3606–3613 (2019).

[22] W. Zhang, R. Li, T. Zeng, Q. Sun, S. Kumar, J. Ye, S. Ji, "Deep model based transfer and multi-task learning for biological image analysis," IEEE Trans. Big Data 6(2), 322–333 (2016).

[23] J. Yosinski, J. Clune, Y. Bengio, H. Lipson, "How transferable are features in deep neural networks?," arXiv:1411.1792.

[24] J. Padarian, B. Minasny, A. McBratney, "Transfer learning to localise a continental soil vis-nir calibration model," Geoderma 340, 279–288 (2019).

[25] D. P. Kingma, J. Ba, Adam: A method for stochastic optimization, arXiv:1412.6980.