Publications

Found 104 results
2021
Lee HGi, Scholle E, Al'Aref S, Beecy A, Peng Y.  2021.  Leveraging Deep Representations of Radiology Reports in Survival Analysis for Predicting Heart Failure Patient Mortality. NAACL.
Chen Q, Keenan TDL, Allot A, Peng Y, Agrón E, Domalpally A, Klaver CCW, Luttikhuizen DT, Colyer MH, Cukras CA et al..  2021.  Multimodal, multitask, multiattention (M3) deep learning detection of reticular pseudodrusen: Toward automated and accessible classification of age-related macular degeneration.. J Am Med Inform Assoc.
Ghahramani G, Brendel M, Lin M, Chen Q, Keenan T, Chen K, Chew E, Lu Z, Peng Y, Wang F.  2021.  Multi-task deep learning-based survival analysis on the prognosis of late AMD using the longitudinal data in AREDS.. AMIA Annu Symp Proc. 2021:506-515.
Islamaj R, Leaman R, Kim S, Kwon D, Wei C-H, Comeau DC, Peng Y, Cissel D, Coss C, Fisher C et al..  2021.  NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature.. Sci Data. 8(1):91.
Han Y, Chen C, Tewfik AH, Ding Y, Peng Y.  2021.  Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning. IEEE International Symposium on Biomedical Imaging (ISBI).
Jaiswal A, Tang L, Ghosh M, Rousseau J, Peng Y, Ding Y.  2021.  RadBERT-CL: Factually-Aware Contrastive Learning for Radiology Report Classification. Machine Learning for Health (ML4H). :196-208.
Sun Q, Peng Y, Liu J.  2021.  A reference-free approach for cell type classification with scRNA-seq.. iScience. 24(8):102855.
Jaiswal A, Li T, Zander C, Han Y, Rousseau JF, Peng Y, Ding Y.  2021.  SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. The IEEE International Conference on Data Mining (ICDM).
Han Y, Chen C, Tang L, Lin M, Jaiswal A, Wang S, Tewfik A, Shih G, Ding Y, Peng Y.  2021.  Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays.. AMIA Annu Symp Proc. 2021:546-555.
He X, Zhang R, Alpert J, Zhou S, Adam TJ, Raisa A, Peng Y, Zhang H, Guo Y, Bian J.  2021.  When text simplification is not enough: could a graph-based visualization facilitate consumers' comprehension of dietary supplement information? JAMIA Open. 4(1):ooab026.
2020
Tang Y-X, Tang Y-B, Peng Y, Yan K, Bagheri M, Redd BA, Brandon CJ, Lu Z, Han M, Xiao J et al..  2020.  Automated abnormality classification of chest radiographs using deep convolutional neural networks. NPJ Digit Med. 3:70.
Peng Y, Lee S, Elton DC, Shen T, Tang Y-xing, Chen Q, Wang S, Zhu Y, Summers R, Lu Z.  2020.  Automatic recognition of abdominal lymph nodes from clinical text. Proceedings of the 3rd Clinical Natural Language Processing Workshop.
Paul A, Shen TC, Balachandar N, Tang Y, Peng Y, Lu Z, Summers RM.  2020.  COMe-SEE: Cross-modality Semantic Embedding Ensemble for Generalized Zero-Shot Diagnosis of Chest Radiographs. Procceddings of the Workshop on Medical Image Learning with Less Labels and Imperfect Data (MIL3ID). :103-111.
Keenan TDL, Chen Q, Peng Y, Domalpally A, Agrón E, Hwang CK, Thavikulwat AT, Lee DH, Li D, Wong WT et al..  2020.  Deep Learning Automated Detection of Reticular Pseudodrusen from Fundus Autofluorescence Images or Color Fundus Photographs in AREDS2. Ophthalmology.
Keenan TDL, Chen Q, Peng Y, Domalpally A, Agrón E, Hwang CK, Thavikulwat ATherese, Lee DHana, Li D, Wong WT et al..  2020.  Deep learning automated detection of reticular pseudodrusen from fundus autofluorescence images and color fundus photographs in the Age-Related Eye Disease Study 2 (AREDS2) . Investigative Ophthalmology & Visual Science. 61:1644.
Peng Y, Chen Q, Lu Z.  2020.  An Empirical Study of Multi-Task Learning on BERT for Biomedical Text Mining. Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing.
Yeganova L, Islamaj R, Chen Q, Leaman R, Allot A, Wei C-H, Comeau DC, Kim W, Peng Y, W. Wilbur J et al..  2020.  Navigating the landscape of COVID-19 research through literature analysis: A bird's eye view. KDD AI for COVID.
Peng Y, Keenan TD, Chen Q, Agrón E, Allot A, Wong WT, Chew EY, Lu Z.  2020.  Predicting risk of late age-related macular degeneration using deep learning. NPJ Digit Med. 3:111.
2019
Wang X, Peng Y, Lu L, Lu Z, Summers RM.  2019.  Automatic Classification and Reporting of Multiple Common Thorax Diseases Using Chest Radiographs. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics. Advances in Computer Vision and Pattern Recognition. :393-412.
Chen Q, Peng Y, Lu Z.  2019.  BioSentVec: creating sentence embeddings for biomedical texts. IEEE International Conference on Healthcare Informatics (ICHI).
Wang X, Peng Y, Lu L, Lu Z, Bagheri M, Summers RM.  2019.  ChestX-ray: Hospital-Scale Chest X-ray Database and Benchmarks on Weakly Supervised Classification and Localization of Common Thorax Diseases. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics. :369-392.
Yan K, Peng Y, Lu Z, Summers RM.  2019.  Fine-Grained Lesion Annotation in CT Images With Knowledge Mined From Radiology Reports. IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019). :285-288.
Du J, Chen Q, Peng Y, Xiang Y, Tao C, Lu Z.  2019.  ML-Net: multi-label classification of biomedical texts with deep neural networks. J Am Med Inform Assoc. 26(11):1279-1285.
Yan K, Tang Y, Peng Y, Sandfort V, Bagheri M, Lu Z, Summers RM.  2019.  MULAN: Multitask Universal Lesion Analysis Network for Joint Lesion Detection, Tagging, and Segmentation. Medical Image Computing and Computer Assisted Intervention – MICCAI. 11769:194-202.
Chen Q, Peng Y, Keenan T, Dharssi S, N EAgro, Wong WT, Chew EY, Lu Z.  2019.  A multi-task deep learning model for the classification of Age-related Macular Degeneration. AMIA Jt Summits Transl Sci Proc. 2019:505-514.