Fan, Yong - The University of Pennsylvania - Perelman School of Medicine

个人简介

Education: PhD (Pattern Recognition And Intelligent Systems) Chinese Academy Of Sciences, Beijing, China, 2003. Description of Research Expertise Dr. Fan has a broad background in medical image analysis and pattern recognition, with specific training in applied mathematics, statistics, and machine learning.

研究领域

His research interests are in the field of imaging analytics, machine learning, pattern recognition, and more generally in computational imaging. Much of his work has been focusing on methodology development and applications of machine learning techniques that quantify morphology and function from medical images, integrate multimodal information to aid diagnosis and prediction of clinical outcomes, and guide personalized treatments. The methodological focus has been on the general field of artificial intelligence, with emphasis on machine learning methods applied to complex and large imaging and clinical data. The image analytic methods being and to be developed include functional connectomics, radiomics, image registration and segmentation, and personalized neuromodulatory therapies. On the clinical side, his primary focus is on applications in clinical neuroscience, in cancer, and in chronic kidney disease, aiming to develop precision diagnostic tools using machine learning and pattern recognition techniques. The clinical research studies include brain development, brain diseases such as Alzheimer's, schizophrenia, depression, and addiction, pediatric kidney diseases, and predictive modeling of treatment outcomes of cancer patients such as rectal and lung cancers.

近期论文

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Shi Yin, Qinmu Peng, Hongming Li, Zhengqiang Zhang, Xinge You, Katherine Fischer, Susan L. Furth, Yong Fan, Gregory E. Tasian: Multi-instance deep learning of ultrasound imaging data for pattern classification of congenital abnormalities of the kidney and urinary tract in children. Urology May 2020 Notes: https://doi.org/10.1016/j.urology.2020.05.019. Hongming Li, Yong Fan: Interpretable, highly accurate brain decoding of subtly distinct brain states from functional MRI using intrinsic functional networks and long short-term memory recurrent neural networks. Neuroimage 202(15): 1-11, Nov 2019 Notes: https://doi.org/10.1016/j.neuroimage.2019.116059. Qiang Zheng, Maxim Itkin, Yong Fan: Quantification of thoracic lymphatic flow patterns using dynamic contrast-enhanced MR lymphangiography. Radiology Page: 1-6, Feb 2020 Notes: https://doi.org/10.1148/radiol.2020192337. Shi Yin, Qinmu Peng, Hongming Li, Zhengqiang Zhang, Xinge You, Katherine Fischer, Susan L Furth, Gregory E Tasian, Yong Fan: Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networks. Medical Image Analysis 60(101602): 1-14, Nov 2019 Notes: https://doi.org/10.1016/j.media.2019.101602. Ariana L. Smith, Steven J. Weissbart, Siobhán M. Hartigan, Michel Bilello, Diane K. Newman, Alan J. Wein, Anna P. Malykhina, Guray Erus, Yong Fan: Association Between Urinary Symptom Severity and White Matter Plaque Distribution in Women with Multiple Sclerosis. Neurourology and Urodynamics 39(1): 339-346, Jan 2020 Notes: https://doi.org/10.1002/nau.24206. Hongming Li, Mohamad Habes, David A. Wolk, Yong Fan: A deep learning model for early prediction of Alzheimer’s disease dementia based on hippocampal magnetic resonance imaging data. Alzheimer's & Dementia: The Journal of the Alzheimer's Association 15(8): 1059-1070, Aug 2019 Notes: https://doi.org/10.1016/j.jalz.2019.02.007. Rixing Jing, Peng Li, Zengbo Ding, Xiao Lin, Rongjiang Zhao, Le Shi, Hao Yan, Jinmin Liao, Chuanjun Zhuo, Lin Lu, Yong Fan: Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients. Human Brain Mapping 40(13): 3930-3939, Aug 2019 Notes: https://doi.org/10.1002/hbm.24678. Reagan R. Wetherill, Hengyi Rao, Nathan Hager, Jieqiong Wang, Teresa R. Franklin, Yong Fan: Classifying and Characterizing Nicotine Use Disorder with High Accuracy Using Machine Learning and Resting-State fMRI. Addiction Biology 24(4): 811-821, Jun 2019 Notes: https://doi.org/10.1111/adb.12644. Hongming Li, Maya Galperin-Aizenberg, Daniel Pryma, Charles B. Simone II, and Yong Fan : Unsupervised machine learning of radiomic features for predicting treatment response and overall survival of early stage non-small cell lung cancer patients treated with stereotactic body radiation therapy. Radiotherapy & Oncology 129(2): 218-226, Nov 2018 Notes: https://doi.org/10.1016/j.radonc.2018.06.025. Xiaofeng Zhu, Weihong Zhang, Yong Fan: A robust reduced rank graph regression method for neuroimaging genetics analysis. Neuroinformatics 16(3-4): 351-361, Oct 2018 Notes: https://doi.org/10.1007/s12021-018-9382-0. Xiaomei Zhao, Yihong Wu, Guidong Song, Zhenye Li, Yazhuo Zhang, and Yong Fan: A deep learning model integrating FCNNs and CRFs for brain tumor segmentation. Medical Image Analysis 43: 98-111, Jan 2018 Notes: https://doi.org/10.1016/j.media.2017.10.002. Yongsheng Han, Hewei Cheng, Jon B. Toledo, Xun Wang, Bo Li, Yongzhu Han, Kai Wang, Yong Fan: Impaired functional default mode network in patients with mild neurological Wilson's disease. Parkinsonism and Related Disorders 30: 46-51, Sep 2016. Hancan Zhu, Hewei Cheng, Xuesong Yang, and Yong Fan: Metric Learning for Multi-atlas based Segmentation of Hippocampus. Neuroinformatics 15(1): 41–50, Jan 2017. Hongming Li, Theodore D. Satterthwaite, and Yong Fan: Large-scale sparse functional networks from resting state fMRI. Neuroimage 156: 1-13, Aug 2017 Notes: https://doi.org/10.1016/j.neuroimage.2017.05.004. Hanyang Peng and Yong Fan: Feature Selection by Optimizing a Lower Bound of Conditional Mutual Information. Information Sciences 418-419: 652-667, Dec 2017. Qiang Zheng, Susan L. Furth, Gregory E. Tasian, Yong Fan: Computer aided diagnosis of congenital abnormalities of the kidney and urinary tract in children based on ultrasound imaging data by integrating texture image features and deep transfer learning image features. Journal of Pediatric Urology 15(1): 75.e1-75.e7, Feb 2019 Notes: https://doi.org/10.1016/j.jpurol.2018.10.020. Rixing Jing, Yongsheng Han, Hewei Cheng, Yongzhu Han, Kai Wang, Daniel Weintraub, Yong Fan: Altered large-scale functional brain networks in neurological Wilson’s disease. Brain Imaging and Behavior Page: 1-11, Apr 2019 Notes: https://doi.org/10.1007/s11682-019-00066-y. Peng Li, Ri-Xing Jing, Rong-Jiang Zhao, Le Shi, Hong-Qiang Sun, Zengbo Ding, Xiao Lin, Lin Lu, Yong Fan: Association between functional and structural connectivity of the corticostriatal network in people with schizophrenia and unaffected first-degree relatives. Journal of Psychiatry and Neuroscience May 2020 Notes: doi:10.1503/jpn.190015.