Publications

Jaiswal A, Chen T, Rousseau JF, Peng Y, Ding Y, Wang Z.  2023.  Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances.. IEEE Winter Conf Appl Comput Vis. 2023:4976-4985.

Jaiswal A, Li T, Zander C, Han Y, Rousseau JF, Peng Y, Ding Y.  2021.  SCALP - Supervised Contrastive Learning for Cardiopulmonary Disease Classification and Localization in Chest X-rays using Patient Metadata. The IEEE International Conference on Data Mining (ICDM).

Jaiswal A, Tang L, Ghosh M, Rousseau J, Peng Y, Ding Y.  2021.  RadBERT-CL: Factually-Aware Contrastive Learning for Radiology Report Classification. Machine Learning for Health (ML4H). :196-208.

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.

Holste G, Wang S, Jiang Z, Shen TC, Shih G, Summers RM, Peng Y, Wang Z.  2022.  Long-Tailed Classification of Thorax Diseases on Chest X-Ray: A New Benchmark Study.. Data Augment Label Imperfections (2022). 13567:22-32.

Holste G, Jiang Z, Jaiswal A, Hanna M, Minkowitz S, Legasto AC, Escalon JG, Steinberger S, Bittman M, Shen TC et al..  2023.  How Does Pruning Impact Long-Tailed Multi-label Medical Image Classifiers? Med Image Comput Comput Assist Interv. 14224:663-673.

He X, Zhang R, Alpert J, Zhou S, Adam TJ, Raisa A, Peng Y, Zhang H, Guo Y, Bian J.  2021.  When text simplification is not enough: could a graph-based visualization facilitate consumers' comprehension of dietary supplement information? JAMIA Open. 4(1):ooab026.

Han Y, Chen C, Tewfik A, Glicksberg B, Ding Y, Peng Y, Wang Z.  2022.  Knowledge-Augmented Contrastive Learning for Abnormality Classification and Localization in Chest X-rays with Radiomics using a Feedback Loop.. IEEE Winter Conf Appl Comput Vis. 2022:1789-1798.

Han Y, Holste G, Ding Y, Tewfik A, Peng Y, Wang Z.  2022.  Radiomics-Guided Global-Local Transformer for Weakly Supervised Pathology Localization in Chest X-Rays.. IEEE Trans Med Imaging. PP

Han Y, Chen C, Tewfik AH, Ding Y, Peng Y.  2021.  Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning. IEEE International Symposium on Biomedical Imaging (ISBI).

Han Y, Chen C, Tang L, Lin M, Jaiswal A, Wang S, Tewfik A, Shih G, Ding Y, Peng Y.  2021.  Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays.. AMIA Annu Symp Proc. 2021:546-555.

Han Z, Shen M, Liu H, Peng Y.  2022.  Topical and emotional expressions regarding extreme weather disasters on social media: a comparison of posts from official media and the public.. Humanit Soc Sci Commun. 9(1):421.

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.

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.

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.

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.

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, 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

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.

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

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, 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.

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.