Publications

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.

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.

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.

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.

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.

Peng Y, Zhang Z, Wang X, Yang L, Lu L.  2019.  Text Mining and Deep Learning for Disease Classification. Handbook of Medical Image Computing and Computer Assisted Intervention. :109-136.

Allot A, Peng Y, Wei C-H, Lee K, Phan L, Lu Z.  2018.  LitVar: a semantic search engine for linking genomic variant data in PubMed and PMC. Nucleic Acids Res. 46(W1):W530-W536.

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 .

Peng Y, Wang X, Lu L, Bagheri M, Summers R, Lu Z.  2018.  NegBio: a high-performance tool for negation and uncertainty detection in radiology reports. AMIA Jt Summits Transl Sci Proc. 2017:188-196.

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow P-M, Zietz M, Hoffman MM et al..  2018.  Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface. 15(141)

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow P-M, Zietz M, Hoffman MM et al..  2018.  Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface. 15(141)

Ching T, Himmelstein DS, Beaulieu-Jones BK, Kalinin AA, Do BT, Way GP, Ferrero E, Agapow P-M, Zietz M, Hoffman MM et al..  2018.  Opportunities and obstacles for deep learning in biology and medicine. J R Soc Interface. 15(141)

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.

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.

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.

Wei C-H, Peng Y, Leaman R, Davis APeter, Mattingly CJ, Li J, Wiegers TC, Lu Z.  2016.  Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task. Database (Oxford). 2016

Wei C-H, Peng Y, Leaman R, Davis APeter, Mattingly CJ, Li J, Wiegers TC, Lu Z.  2016.  Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task. 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

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

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, Wei C-H, Lu Z.  2016.  Improving chemical disease relation extraction with rich features and weakly labeled data. J Cheminform. 8:53.

Peng Y, Arighi C, Wu CH,.Vijay-Shanker K.  2015.  Extended dependency graph for BioC-compatible protein-protein interaction (PPI) passage detection in full-text articles. Proceedings of the BioCreative V Workshop. :30-35.

Peng Y, Gupta S, Wu C, Shanker V.  2015.  An extended dependency graph for relation extraction in biomedical texts. Proceedings of BioNLP 15. :21–30.