Cai Chengfei

Educational experience

Undergraduate 2012/09/08-2016/06/20 Nanjing University of Information Science & Technology

Master 2016/09/07-2019/06/20 Nanjing University of Information Science & Technology

PhD 2022/09/12- present Nanjing University of Information Science & Technology

Relevant experience

2019/07/15 2019/11/30 Suzhou Keda Technology Co., Ltd. Algorithm R&D

2019/12/01 2021/4/30 Shanghai Anwell Information Technology Co., Ltd. Algorithm Research and Development

2021/08/15 to present Taizhou College full-time teacher

Skills

Python, Matlab, C, C++, R and other computer languages

research project

Use artificial intelligence technology to conduct research on digestive tract diseases, such as histological grading of inflammatory bowel disease activity and predicting patient clinical grade scores, prognostic analysis of multi-modal colorectal cancer and neoadjuvant treatment response, gastric cancer, kidney and other related research

Paper results

[1] Cai Chengfei, Xu Jun, Liang Li, et al. Multiple tissue segmentation of colorectal full scan pathological images based on deep convolutional network [J]. Chinese Journal of Biomedical Engineering, 2017, 36(5):5.

[ 2] Xu J , Cai C , Zhou Y , et al. Multi-tissue Partitioning for Whole Slide Images of Colorectal Cancer Histopathology Images with Deeptissue Net[J]. Springer, Cham, 2019.

[3] Yan, C., Xu, J., Xie, J., Cai, C ., & Lu, H. (2020, April). Prior-Aware CNN with Multi-Task Learning for Colon Images Analysis. In 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI) (pp. 254-257). IEEE.

[4] Jun Xu, Andrew Janowczyk, Laura M. Barisoni,, Chengfei Ca i*, Jeffrey Nirschl, Matthew Palmer, Michael D. Feldman, D Chen, John O’Toole, Z Zaky, Emilio Poggio, John R. Sedor, and Anant Madabhushi, “Predicting APOL1 risk category from kidney donor biopsies using deep learning”, American Society of Nephrology (ASN) Kidney Week, 2018

[5] Wang Quan, Shen Qin, Zhang Zelin, Cai Chengfei, Lu Haoda, Zhou Xiaojun, Xu Jun. Lung cancer gene mutation prediction based on deep learning and tissue morphology analysis [J]. Journal of Biomedical Engineering, 2020, 37(01):10-18.

Patent: [1] Name: Colorectal panoramic digital pathology image tissue segmentation method based on deep network, inventor: Xu Jun; Cai Chengfei; Xu Haijun; Sun Mingjian, application number: 201710516329.7, publication number: 107665492A, authorization number: 107665492B

Translated from the original Chinese source.