Publications

Sun Z, Lin M, Zhu Q, Xie Q, Wang F, Lu Z, Peng Y.  2023.  A scoping review on multimodal deep learning in biomedical images and texts.. J Biomed Inform. 146:104482.

Wang S, Lin M, Ding Y, Shih G, Lu Z, Peng Y.  2022.  Radiology Text Analysis System (RadText): Architecture and Evaluation.. IEEE Int Conf Healthc Inform. 2022:288-296.

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.

Lee J, Wanyan T, Chen Q, Keenan TDL, Glicksberg BS, Chew EY, Lu Z, Wang F, Peng Y.  2022.  Predicting Age-related Macular Degeneration Progression with Longitudinal Fundus Images Using Deep Learning.. Mach Learn Med Imaging. 13583:11-20.

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)

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.

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.

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.

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.

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.

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.

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.

Lin M, Li T, Yang Y, Holste G, Ding Y, Van Tassel SH, Kovacs K, Shih G, Wang Z, Lu Z et al..  2023.  Improving model fairness in image-based computer-aided diagnosis.. Nat Commun. 14(1):6261.

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

Wang S, Zhu Y, Lee S, Elton DC, Shen TC, Tang Y, Peng Y, Lu Z, Summers RM.  2022.  Global-Local attention network with multi-task uncertainty loss for abnormal lymph node detection in MR images.. Med Image Anal. 77:102345.

Paul A, Shen TC, Lee S, Balachandar N, Peng Y, Lu Z, Summers RM.  2021.  Generalized Zero-shot Chest X-ray Diagnosis through Trait-Guided Multi-view Semantic Embedding with Self-training.. IEEE Trans Med Imaging.

Peng Y, Rios A, Kavuluru R, Lu Z.  2018.  Extracting chemical-protein relations with ensembles of SVM and deep learning models. Database (Oxford). 2018

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.

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.

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.

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.

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

Ghahramani GC, Brendel M, Chen Q, Keenan TD, Chen K, Chew EY, Lu Z, Peng Y, Wang F.  2021.  Deep learning survival analysis on the progression to late AMD in the Age-Related Eye Disease Study. Investigative Ophthalmology & Visual Science.