Publications

Found 41 results
Filters: First Letter Of Last Name is X  [Clear All Filters]
2023
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.
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.
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  Confidence Score: A Data-Driven Measure for Inclusive Systematic Reviews Considering Unpublished Preprints..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.
Lin M, Xiao Y, Hou B, Wanyan T, Sharma MManoj, Wang Z, Wang F, Van Tassel S, Peng Y.  2023.  Evaluate underdiagnosis and overdiagnosis bias of deep learning model on primary open-angle glaucoma diagnosis in under-served populations.. AMIA Jt Summits Transl Sci Proc. 2023:370-377.
Tang L, Sun Z, Idnay B, Nestor JG, Soroush A, Elias PA, Xu Z, Ding Y, Durrett G, Rousseau JF et al..  2023.  Evaluating large language models on medical evidence summarization.. NPJ Digit Med. 6(1):158.
Wang S, Dang Y, Sun Z, Ding Y, Pathak J, Tao C, Xiao Y, Peng Y.  2023.  An NLP approach to identify SDoH-related circumstance and suicide crisis from death investigation narratives.. J Am Med Inform Assoc.
Adekkanattu P, Rasmussen LV, Pacheco JA, Kabariti J, Stone DJ, Yu Y, Jiang G, Luo Y, Brandt PS, Xu Z et al..  2023.  Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study.. Sci Rep. 13(1):294.
Adekkanattu P, Rasmussen LV, Pacheco JA, Kabariti J, Stone DJ, Yu Y, Jiang G, Luo Y, Brandt PS, Xu Z et al..  2023.  Prediction of left ventricular ejection fraction changes in heart failure patients using machine learning and electronic health records: a multi-site study.. Sci Rep. 13(1):294.
Keloth VK, Banda JM, Gurley M, Heider PM, Kennedy G, Liu H, Liu F, Miller T, Natarajan K, Patterson OV et al..  2023.  Representing and Utilizing Clinical Textual Data for Real World Studies: An OHDSI Approach.. J Biomed Inform. :104343.
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.
2022
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.
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.
2020
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.
2019
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.
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)