Publications

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.

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.

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.

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.

Doğan RIslamaj, Chatr-aryamontri A, Kim S, Wei C-H, Peng Y, Comeau D, Lu Z.  2017.  BioCreative VI Precision Medicine Track: creating a training corpus for mining protein-protein interactions affected by mutations. BioNLP 2017. :171–175.

Chen Q, Peng Y, Lu Z.  2019.  BioSentVec: creating sentence embeddings for biomedical texts. IEEE International Conference on Healthcare Informatics (ICHI).

Peng Y, Rios A, Kavuluru R, Lu Z.  2017.  Chemical-protein relation extraction with ensembles of SVM, CNN, and RNN models. Proceedings of the BioCreative VI Workshop. :148-151.

Wang X, Peng Y, Lu L, Lu Z, Bagheri M, Summers RM.  2017.  ChestX-Ray8: Hospital-Scale Chest X-Ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases. IEEE Conference on Computer Vision and Pattern Recognition (CVPR). :2097-2106.

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 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, Lu Z.  2017.  Deep learning for extracting protein-protein interactions from biomedical literature. BioNLP 2017. :29–38.

Mathai TSudharshan, Lee S, Elton DC, Shen TC, Peng Y, Lu Z, Summers RM.  2021.  Detection of lymph nodes in T2 MRI using neural network ensembles. Learning in Medical Imaging (MLMI). :682-691.

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.

Yan K, Peng Y, Sandfort V, Bagheri M, Lu Z, Summers RM.  0.  Holistic and Comprehensive Annotation of Clinically Significant Findings on Diverse CT Images: Learning From Radiology Reports and Label Ontology. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). :8523-8532.

Paul A, Shen TC, Peng Y, Lu Z, Summers RM.  2021.  Learning few-shot chest X-ray diagnosis using images from the published scientific literature. IEEE International Symposium on Biomedical Imaging (ISBI).

Mathai TSudharshan, Lee S, Elton DC, Shen TC, Peng Y, Lu Z, Summers RM.  2022.  Lymph node detection in T2 MRI with transformers. SPIE Medical Imaging. :120333B.

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.

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.

Wei C-H, Peng Y, Leaman R, Davis APeter, Mattingly CJ, Li J, Wiegers TC, Lu Z.  2015.  Overview of the Biocreative V chemical disease relation (CDR) task. Proceedings of the BioCreative V Workshop. :154-166.

Peng Y, Yan K, Sandfort V, Summers RM, Lu Z.  2019.  A self-attention based deep learning method for lesion attribute detection from CT reports. 2019 IEEE International Conference on Healthcare Informatics (ICHI).

Wang X, Peng Y, Lu L, Lu Z, Summers RM.  2018.  TieNet: Text-Image Embedding Network for Common Thorax Disease Classification and Reporting in Chest X-Rays. IEEE/CVF Conference on Computer Vision and Pattern Recognition. :9049-9058.

Peng Y, Yan S, Lu Z.  2019.  Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets. Proceedings of the 18th BioNLP Workshop and Shared Task. :58–65.

Peng Y, Tang Y, Lee S, Zhu Y, Summers RM, Lu Z.  2021.  COVID-19-CT-CXR: A Freely Accessible and Weakly Labeled Chest X-Ray and CT Image Collection on COVID-19 From Biomedical Literature. IEEE Transactions on Big Data. 7(1):3-12.

Wang X, Peng Y, Lu L, Lu Z, Summers RM.  2018.  Method and system of building hospital-scale chest x-ray database for entity extraction and weakly-supervised classification and localization of common thorax diseases .

Johnson AEW, Pollard TJ, Greenbaum NR, Lungren MP, Deng C-ying, Peng Y, Lu Z, Mark RG, Berkowitz SJ, Horng S.  0.  MIMIC-CXR-JPG, a large publicly available database of labeled chest radiographs.