Publications

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.

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

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

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.

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.

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

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)

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Brandt PS, Pacheco JA, Adekkanattu P, Sholle ET, Abedian S, Stone DJ, Knaack DM, Xu J, Xu Z, Peng Y et al..  2022.  Design and validation of a FHIR-based EHR-driven phenotyping toolbox.. J Am Med Inform Assoc. 29(9):1449-1460.