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Dr. Fan has a broad background in medical image analysis and pattern recognition, with specific training in applied mathematics, statistics, and machine learning. 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.
Yuemeng Li, Hongming Li, Yong Fan: ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation Medical Image Analysis 70 (101991): 1-12,2021.
Zhicheng Jiao, Hongming Li, Ying Xiao, Charu Aggarwal, Maya Galperin-Aizenberg, Daniel Pryma, Charles B. Simone, II, Steven J. Feigenberg, Gary D. Kao, Yong Fan: Integration of Risk Survival Measures Estimated From Pre- and Posttreatment Computed Tomography Scans Improves Stratification of Patients With Early-Stage Non-small Cell Lung Cancer Treated With Stereotactic Body Radiation Therapy International Journal of Radiation Oncology, Biology, Physics 109 (5): 1647-1656,2021.
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 142 : 183-189,2020.
Qiang Zheng, Maxim Itkin, Yong Fan: Quantification of thoracic lymphatic flow patterns using dynamic contrast-enhanced MR lymphangiography Radiology 296 (1): 202-207,2020.
Hangfan Liu, Hongming Li, Mohamad Habes, Yuemeng Li, Pamela Boimel, James Janopaul-Naylor, Ying Xiao, Edgar Ben-Josef, and Yong Fan: Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis IEEE Transactions on Biomedical Engineering 67 (10): 2735-2744,2020.
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): 339-346,2020.
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): 1-11,2019.
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): 101602,2020.
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): 3930-3939,2019.
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): 1059-1070,2019.
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): 811-821,2019.
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): 218-226,2018.
Xiaofeng Zhu, Weihong Zhang, Yong Fan: A robust reduced rank graph regression method for neuroimaging genetics analysis Neuroinformatics 16 (3-4): 351-361,2018.
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 : 98-111,2018.
Zaixu Cui, Hongming Li, Cedric H Xia, Bart Larsen, Azeez Adebimpe, Graham L Baum, Matt Cieslak, Raquel E Gur, Ruben C Gur, Tyler M Moore, Desmond J Oathes, Aaron F Alexander-Bloch, Armin Raznahan, David R Roalf, Russell T Shinohara, Daniel H Wolf, Christos Davatzikos, Danielle S Bassett, Damien A Fair, Yong Fan, Theodore D Satterthwaite: Individual variation in functional topography of association networks in youth Neuron 106 (2): 340-353,2020.
Hewei Cheng, Lu Gao, Bo Hou, Feng Feng, Xiaopeng Guo, Zihao Wang, Ming Feng, Bing Xing, and Yong Fan: Reversibility of Cerebral Blood Flow in Patients with Cushing's Disease after Surgery Treatment Metabolism 104 (154050): 1-7,2020.
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 45 (6): 395-405,2020.
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 : 1-11,2019.
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.e7,2019.
Hanyang Peng and Yong Fan: Feature Selection by Optimizing a Lower Bound of Conditional Mutual Information Information Sciences 418-419 : 652-667,2017.
Hongming Li, Theodore D. Satterthwaite, and Yong Fan: Large-scale sparse functional networks from resting state fMRI Neuroimage 156 : 1-13,2017.
Hancan Zhu, Hewei Cheng, Xuesong Yang, and Yong Fan: Metric Learning for Multi-atlas based Segmentation of Hippocampus Neuroinformatics 15 (1): 41–50,2017.
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 : 46-51,2016.
Department of RadiologyPerelman School of MedicineUniversity of PennsylvaniaRichards Building, 7th floor3700 Hamilton Walk