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Publications

Rajpurkar P, Irvin J,  Zhu K, Ball R, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz C, Shpanskaya K, Lungren MP, Ng AY. MURA Dataset: Towards Radiologist-Level Abnormality Detection in Musculoskeletal Radiographs  arXiv:1712.06957


Banerjee I, Chen MC, Lungren MP, Rubin DL Radiology Report Annotation using Intelligent Word Embeddings: Applied to Multi-institutional Chest CT Cohort. Journal of Biomedical Informatics.


Rajpurkar P, Irvin J,  Zhu K, Yang B, Mehta H, Duan T, Ding D, Bagul A, Langlotz C, Shpanskaya K, Lungren MP, Ng AY.  CheXNet: Radiologist-Level Pneumonia Detection on Chest X-Rays with Deep Learning  arXiv:1711.05225v1


Chen MC, Ball RL, Yang L, Moradzadeh N, Chapman B, Larson DB, Langlotz CP, Amrhein TJ, Lungren MP. Deep learning to Classify Radiology Free Text Reports. Radiology .2017 Nov 13:171115.


Larson DB, Chen MC, Lungren MP, Halabi SS, Stence NV, Langlotz CP. Performance of a deep learning neural network model in assessing skeletal maturity on pediatric hand radiographs. Radiology 2017 Nov 2:170236.


Do BH Langlotz C Beaulieu CF. Bone Tumor Diagnosis Using a Naïve Bayesian Model of Demographic and Radiographic Features. J Digit Imaging2017 Oct;30(5):640-647


Hassanpour, S., Langlotz, C. P. Information extraction from multi-institutional radiology reports. Artif Intell Med 2016 Jan;66:29-39.


Hassanpour S, Langlotz CP, Amrhein TJ, Befera NT, Lungren MPPerformance of a Machine Learning Classifier of Knee MRI Reports in Two Large Academic Radiology Practices: A Tool to Estimate Diagnostic Yield. AJR Am J Roentgenol. 2017 Apr;208(4):750-753. 


Hassanpour SBay GLanglotz CP. Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing. J Digit Imaging. 2017 Jun;30(3):314-322.


Zhou M, Leung A, Echegaray S, Gentles A, Shrager JB, Jensen KC, Berry GJ, Plevritis SK, Rubin DL, Napel S, Gevaert O. Non-Small Cell Lung Cancer Radiogenomics Map Identifies Relationships between Molecular and Imaging Phenotypes with Prognostic Implications. Radiology. 2018 Jan;286(1):307-315.


de Sisternes L Jonna G, Moss J, Marmor MF, Leng T, Rubin DL.  Automated intraretinal segmentation of SD-OCT images in normal and age-related macular degeneration eyes. Biomed Opt Express. 2017 Feb 28;8(3):1926-1949.


Wang S, Zhou M, Liu Z, Liu Z, Gu D, Zang Y, Dong D, Gevaert O, Tian J. Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation. Med Image Anal. 2017 Aug;40:172-183.


Echegaray S, Nair V, Kadoch M, Leung A, Rubin D, Gevaert O, Napel S. A Rapid Segmentation-Insensitive "Digital Biopsy" Method for Radiomic Feature Extraction: Method and Pilot Study Using CT Images of Non-Small Cell Lung Cancer. Tomography. 2016 Dec;2(4):283-294.


Hassanpour S, Bay G, Langlotz CP. Characterization of Change and Significance for Clinical Findings in Radiology Reports Through Natural Language Processing. J Digit Imaging. 2017 Jun;30(3):314-322.


Wang S, Zhou M, Gevaert O, Tang Z, Dong D, Liu Z, Tian J.  A multi-view deep convolutional neural networks for lung nodule segmentation.  Proc IEEE Eng Med Biol Soc. 2017 Jul;2017:1752-1755.