T
Truyen Tran
Researcher at Deakin University
Publications - 223
Citations - 5710
Truyen Tran is an academic researcher from Deakin University. The author has contributed to research in topics: Deep learning & Computer science. The author has an hindex of 32, co-authored 204 publications receiving 3893 citations. Previous affiliations of Truyen Tran include Curtin University.
Papers
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Journal ArticleDOI
Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View.
Wei Luo,Dinh Phung,Truyen Tran,Sunil Gupta,Santu Rana,Chandan Karmakar,Alistair Shilton,John Yearwood,Nevenka Dimitrova,Tu Bao Ho,Svetha Venkatesh,Michael Berk +11 more
TL;DR: A set of guidelines was generated to enable correct application of machine learning models and consistent reporting of model specifications and results in biomedical research and it is believed that such guidelines will accelerate the adoption of big data analysis, particularly with machine learning methods, in the biomedical research community.
Journal ArticleDOI
Predicting healthcare trajectories from medical records: A deep learning approach.
TL;DR: DeepCare is introduced, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes, demonstrating the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction.
Journal ArticleDOI
$\mathtt {Deepr}$: A Convolutional Net for Medical Records.
TL;DR: A new deep learning system that learns to extract features from medical records and predicts future risk automatically achieves superior accuracy compared to traditional techniques, detects meaningful clinical motifs, and uncovers the underlying structure of the disease and intervention space.
Posted Content
DeepCare: A Deep Dynamic Memory Model for Predictive Medicine
TL;DR: DeepCare as discussed by the authors is an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes.
Book ChapterDOI
DeepCare: A Deep Dynamic Memory Model forźPredictive Medicine
TL;DR: The efficacy of DeepCare for disease progression modeling and readmission prediction in diabetes, a chronic disease with large economic burden, is demonstrated and the results show improved modeling and risk prediction accuracy.