Publications

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

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.

Karabulut MEfruz, Vijay-Shanker K., Peng Y.  2021.  CU-UD: text-mining drug and chemical-proteininteractions with ensembles of BERT-based models. BioCreative VII. :45-48.

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.

Tong J, Luo C, Sun Y, Duan R, Saine E, Lin L, Peng Y, Lu Y, Batra A, Pan A et al..  2023.  Confidence Score: A Data-Driven Measure for Inclusive Systematic Reviews Considering Unpublished Preprints.. J Am Med Inform Assoc.

Deng Y, Liu L, Jiang H, Peng Y, Wei Y, Zhou Z, Zhong Y, Zhao Y, Yang X, Yu J et al..  2023.  Comparison of State-of-the-Art Neural Network Survival Models with the Pooled Cohort Equations for Cardiovascular Disease Risk Prediction.. BMC Med Res Methodol. 23(1):22.

Xu J, Wang F, Zang C, Zhang H, Niotis K, Liberman AL, Stonnington CM, Ishii M, Adekkanattu P, Luo Y et al..  2023.  Comparing the effects of four common drug classes on the progression of mild cognitive impairment to dementia using electronic health records.. Sci Rep. 13(1):8102.

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.

Schmeelk S, Dogo MSamuel, Peng Y, Patra BGopal.  2022.  Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing.. Proc Annu Hawaii Int Conf Syst Sci. 2022:4140-4146.

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.

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, 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.

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

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.

Kim S, Doğan RIslamaj, Chatr-Aryamontri A, Chang CS, Oughtred R, Rust J, Batista-Navarro R, Carter J, Ananiadou S, Matos S et al..  2016.  BioCreative V BioC track overview: collaborative biocurator assistant task for BioGRID. Database (Oxford). 2016

Peng Y, Arighi C, Wu CH, Vijay-Shanker K.  2016.  BioC-compatible full-text passage detection for protein-protein interactions using extended dependency graph. Database (Oxford). 2016

Comeau DC, Batista-Navarro RTheresa, Dai H-J, Doğan RIslamaj, Yepes AJimeno, Khare R, Lu Z, Marques H, Mattingly CJ, Neves M et al..  2014.  BioC interoperability track overview. Database (Oxford). 2014

Comeau DC, Doğan RIslamaj, Ciccarese P, Cohen KBretonnel, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M et al..  2013.  BioC: a minimalist approach to interoperability for biomedical text processing. Database (Oxford). 2013:bat064.

Chen Q, Rankine A, Peng Y, Aghaarabi E, Lu Z.  2021.  Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study.. JMIR Med Inform. 9(12):e27386.

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.

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.

Lin M, Hou B, Liu L, Gordon M, Kass M, Wang F, Van Tassel SH, Peng Y.  2022.  Automated diagnosing primary open-angle glaucoma from fundus image by simulating human's grading with deep learning.. Sci Rep. 12(1):14080.

Patra BGopal, Sun Z, Cheng Z, Kumar PKasi Reddy, Altammami A, Liu Y, Joly R, Jedlicka C, Delgado D, Pathak J et al..  2023.  Automated classification of lay health articles using natural language processing: a case study on pregnancy health and postpartum depression.. Front Psychiatry. 14:1258887.

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.