代表性科研成果
[1]Mi Li, Jinyu Zhang, Jie Song, Zijian Li, Shengfu Lu, A Clinical-Oriented Non Severe Depression Diagnosis Method Based on Cognitive Behavior of Emotional Conflict. IEEE Transactions on Computational Social Systems, 2022. (DOI 10.1109/TCSS.2022.3152091, SCI).
[2]Mi Li, Wei Zhang, Bin Hu, Jiaming Kang, Yuqi Wang, Shengfu Lu, Automatic Assessment of Depression and Anxiety through Encoding Pupil-wave from HCI in VR Scenes, ACM Transactions on Multimedia Computing Communications and Applications, 2022. (DOI: http://dx.doi.org/10.1145/3513263, SCI).
[3]Mi Li, Jinyu Zhang, Qian Zhai, Jiaming Kang, Shengfu Lu and Jian Yang. Automated Recognition of Depression from Fewer-shot Leaning in Resting-state fMRI with ReHo Using Deep Convolutional Neural Network. Journal of Mechanics in Medicine and Biology, 21(8), 2021. (SCI)
[4]Shengfu Lu, Xin Shi, Mi Li*, Jinan Jiao, Lei Feng and Gang Wang. Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity. Mathematical Biosciences and Engineering. 18(4): 4586-4602, 2021. (SCI)
[5]Mi Li, Lei Cao, Qian Zhai, Peng Li, Sa Liu, Richeng Li, Lei Feng, Gang Wang, Bin Hu, Shengfu Lu*, Method of depression classification based on behavioral and physiological signals of eye movement, Complexity, 2020, 4174857: 1-9. (SCI)
[6]Mi Li, Huan Chen, Xin Shi, Ming Zhang, Shengfu Lu*. A multi-information fusion “triple variables with iteration” inertia weight PSO algorithm and its application. Applied Soft Computing, 2019, 84: 105677. (SCI)
[7]Mi Li, Huan Chen, Xiaodong Wang, Ning Zhong*, Shengfu Lu*. An improved particle swarm optimization algorithm with adaptive inertia weight. International Journal of Information Technology & Decision Making, 2019, 18(3): 833-866. (SCI)
[8]Mi Li, Hongpei Xu, Shengfu Lu*. Neural basis of depression related to a dominant right hemisphere: a resting-state fMRI study. Behavioral Neurology, 2018, 5024520: 1-10. (SCI)
[9]Mi Li, Lei Cao, Dachao Liu, Leilei Li, Shengfu Lu*. Deep learning based transfer learning for possible facial psychological expression recognition. Journal of Medical Imaging and Health Informatics, 2018, 8(7):1478-1485. (SCI)
[10]Mi Li, Ming Zhang, Huan Chen, Shengfu Lu*. A method of biomedical information classification based on particle swarm optimization with inertia weight and mutation. Open Life Science, 2018, 13: 355-373. (SCI)
[11]Mi Li, Shengfu Lu, Gang Wang, Ning Zhong. Affective bandwidth measurement and affective disorder judgment method. American Invention Patent, 14/731,928. 2017-01-03. (美国发明专利,已授权)
[12]栗觅、胡斌、吕胜富、康嘉明,基于静息态脑功能图像的情绪状态展示方法、装置及系统202111178892.0,2022-01-28. (已授权)
[13]栗觅、胡斌、吕胜富、康嘉明,杨闯,情绪状态展示方法、装置及系统,ZL 202111178893.5,2021-12-28. (已授权)
[14]栗觅,吕胜富,孙建康,王刚,丰雷,钟宁.基于注意和情感信息融合的抑郁诊断系统及数据处理方法.中国发明专利,ZL 201510468260.6. 2018-07-05. (已授权)
[15]栗觅,吕胜富,马理旺,钟宁.一种基于视觉行为的网上用户类型识别方法及系统.中国发明专利, ZL 201510037404.2. 2018-01-12. (已授权)
[16]栗觅,吕胜富,张孟杰,钟宁.一种基于眼动数据的网上用户状态识别方法和装置.中国发明专利, ZL 201510019518.4. 2017-09-19. (已授权)
[17]栗觅,吕胜富,孙建康,王刚,丰雷,钟宁.一种抑郁风险三级预警方法及系统.中国发明专利, ZL 201510018792.X. 2017-06-20. (已授权)
[18]栗觅,吕胜富,周宇,钟宁.一种用于人类认知模式识别的特征归一化方法及系统.中国发明专利, ZL 201410441415.2. 2016-05-11. (已授权)
[19]栗觅,吕胜富,王刚,钟宁.一种情感带宽测定方法和系统.中国发明专利, ZL 201410440520.4. 2015-08-26. (已授权)
[20]栗觅,吕胜富,王静,钟宁.一种视觉注意的检测方法及系统.中国发明专利, ZL 201410441421.8. 2015-08-12. (已授权)
[21]栗觅,张明,吕胜富,吕晓峰,徐季莹,薛佳,刘兴旺,刘大超,钟宁.自适应惯性权重PSO算法优化SVM分类模型系统.软件著作权(2016SR348321),中国,2016-09
[22]栗觅,孙建康,吕胜富,王晓东,钟宁.抑郁症测试诊断系统.软件著作权(2015SR073847),中国,2016-04
[23]栗觅,孙建康,吕胜富,王静,刘鹏飞,钟宁.抑郁评估与辅助诊断系统.软件著作权(2014SR082851),中国,2014-06
[24]栗觅,吕胜富,孙建康,薛佳,王静,钟宁.眼动信息可视化集成处理系统.软件著作权(2014SR087734),中国, 2014-06
所指导毕业研究生中,获得北京工业大学优秀硕士学位论文4人,获研究生国家奖学金3人,北京市及校级优秀毕业生1人。欢迎热衷于人工智能、模式识别以及面向医疗的智能诊断与评估方法与应用等方面研究的学生报考博士、硕士研究生!