Truyen Tran - Google Scholar

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	All	Since 2015
Citations	2675	2461
h-index	27	25
i10-index	58	51

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Co-authors

Svetha VenkateshProfessor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Dinh PhungProfessor, Monash UniversityVerified email at monash.edu
Wei LuoDeakin UniversityVerified email at deakin.edu.au
Trang PhamSoftware Engineer, GoogleVerified email at google.com
Aditya GhoseProfessor of Computer Science, University of WollongongVerified email at uow.edu.au
Hoa Khanh DamAssociate Professor in Software Engineering, University of WollongongVerified email at uow.edu.au
Sunil GuptaAssociate Professor, Deakin UniversityVerified email at deakin.edu.au
Santu RanaAssociate Professor of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Tu Dinh NguyenLead Research Scientist, Trusting SocialVerified email at trustingsocial.com
Michael BerkDeakin UniversityVerified email at deakin.edu.au
Phuoc NguyenAssociate research fellow, Deakin UniversityVerified email at deakin.edu.au
John GrundyAustralian Laureate Fellow and Professor of Software Engineering, Faculty of IT, Monash UniversityVerified email at monash.edu
Kien DoDeakin UniversityVerified email at deakin.edu.au
Hung BuiResearch Scientist, Google DeepMindVerified email at google.com
Thin NguyenSenior Research Fellow, Deakin University, AustraliaVerified email at deakin.edu.au
Morakot Choetkiertikul, Ph.D.Lecture at Faculty of ICT, Mahidol UniversityVerified email at mahidol.ac.th
Chandan KarmakarLecturer of Computer Science, Deakin UniversityVerified email at deakin.edu.au
Hung LeDeakin UniversityVerified email at deakin.edu.au
Vuong LeDeakin UniversityVerified email at deakin.edu.au
Prof Richard J HarveyClinical Professor, Deakin UniversityVerified email at deakin.edu.au

Truyen Tran

Associate Professor, Applied AI Institute, Deakin University

Verified email at deakin.edu.au - Homepage

artificial intelligence machine learning computational biomedicine


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deepr: A convolutional net for medical records P Nguyen, T Tran, N Wickramasinghe, S Venkatesh IEEE journal of biomedical and health informatics 21 (1), 22-30, 2017	186*	2017
DeepCare: A deep dynamic memory model for predictive medicine T Pham, T Tran, D Phung, S Venkatesh PAKDD 6, 26094, 2016	184	2016
Guidelines for developing and reporting machine learning predictive models in biomedical research: A multidisciplinary view W Luo, D Phung, T Tran, S Gupta, S Rana, C Karmakar, A Shilton, ... Journal of medical Internet research 18 (12), 2016	174	2016
Predicting healthcare trajectories from medical records: A deep learning approach T Pham, T Tran, D Phung, S Venkatesh Journal of Biomedical Informatics 69, 218--229, 2017	153	2017
Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM) T Tran, TD Nguyen, D Phung, S Venkatesh Journal of Biomedical Informatics, 2015	108	2015
Column networks for collective classification T Pham, T Tran, D Phung, S Venkatesh AAAI'17, 2017	95	2017
Risk stratification using data from electronic medical records better predicts suicide risks than clinician assessments T Tran, W Luo, D Phung, R Harvey, M Berk, RL Kennedy, S Venkatesh BMC Psychiatry (ECR Best paper awarded by CRESP), 2014	92	2014
Nonnegative shared subspace learning and its application to social media retrieval SK Gupta, D Phung, B Adams, T Tran, S Venkatesh KDD'10, 1169-1178, 2010	88	2010
Ordinal Boltzmann machines for collaborative filtering TT Truyen, DQ Phung, S Venkatesh UAI'09 (Best paper runner up), 548-556, 2009	65	2009
Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry S Gupta, T Tran, W Luo, D Phung, RL Kennedy, A Broad, D Campbell, ... BMJ Open, 2014	55	2014
Automatic feature learning for predicting vulnerable software components HK Dam, T Tran, T Pham, SW Ng, J Grundy, A Ghose IEEE Transactions on Software Engineering, 2018	53*	2018
Lessons learned from using a deep tree-based model for software defect prediction in practice HK Dam, T Pham, SW Ng, T Tran, J Grundy, A Ghose, T Kim, CJ Kim MSR'19, 2019	52*	2019
A deep language model for software code HK Dam, T Tran, T Pham FSE'16 Workshop on Naturalness of Software (NL+SE), 2016	50	2016
A deep learning model for estimating story points M Choetkiertikul, HK Dam, T Tran, T Pham, A Ghose, T Menzies IEEE Transactions on Software Engineering, DOI:10.1109/TSE.2018.2792473, 2018	49	2018
Stabilized sparse ordinal regression for medical risk stratification T Tran, D Phung, W Luo, S Venkatesh Knowledge and Information Systems, 2015	49	2015
Improving generalization and stability of Generative Adversarial Networks H Thanh-Tung, T Tran, S Venkatesh ICLR'19, 2019	45	2019
Mixed-variate restricted Boltzmann machines T Tran, D Phung, S Venkatesh ACML'11, 2011	42	2011
Hierarchical semi-Markov conditional random fields for recursive sequential data T Tran, D Phung, H Bui, S Venkatesh NIPS'08, 2008	42	2008
Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data S Rana, T Tran, W Luo, D Phung, S Venkatesh, RL Kennedy Australian Health Review, 2014	40	2014
A framework for feature extraction from hospital medical data with applications in risk prediction T Tran, W Luo, D Phung, S Gupta, S Rana, RL Kennedy, A Larkins, ... BMC bioinformatics 15 (1), 6596, 2014	38*	2014

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