Thomas P. Quinn

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 20

Top Topics

Medical Students

Top Venues

IEEE ACM Trans. Comput. Biol. Bioinform.

Publications

Tri Minh Nguyen, Thomas P. Quinn, Thin Nguyen, Truyen Tran
Explaining Black Box Drug Target Prediction Through Model Agnostic Counterfactual Samples. IEEE ACM Trans. Comput. Biol. Bioinform. 20 (2) (2023)
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome. NeurIPS (2022)
Thomas P. Quinn, Stephan Jacobs, Manisha Senadeera, Vuong Le, Simon Coghlan
The three ghosts of medical AI: Can the black-box present deliver? Artif. Intell. Medicine 124 (2022)
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome. CoRR (2022)
Thomas P. Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le
A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research. CoRR (2021)
Thin Nguyen, Hang Le, Thomas P. Quinn, Tri Nguyen, Thuc Duy Le, Svetha Venkatesh
GraphDTA: predicting drug-target binding affinity with graph neural networks. Bioinform. 37 (8) (2021)
Thin Nguyen, Samuel C. Lee, Thomas P. Quinn, Buu Minh Thanh Truong, Xiaomei Li, Truyen Tran, Svetha Venkatesh, Thuc Duy Le
PAN: Personalized Annotation-Based Networks for the Prediction of Breast Cancer Relapse. IEEE ACM Trans. Comput. Biol. Bioinform. 18 (6) (2021)
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
Learning sparse log-ratios for high-throughput sequencing data. Bioinform. 38 (1) (2021)
Tri Minh Nguyen, Thomas P. Quinn, Thin Nguyen, Truyen Tran
Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction. CoRR (2021)
Thomas P. Quinn, Manisha Senadeera, Stephan Jacobs, Simon Coghlan, Vuong Le
Trust and medical AI: the challenges we face and the expertise needed to overcome them. J. Am. Medical Informatics Assoc. 28 (4) (2021)
Thomas P. Quinn, Simon Coghlan
Readying Medical Students for Medical AI: The Need to Embed AI Ethics Education. CoRR (2021)
Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient. BioData Min. 14 (1) (2021)
Thomas P. Quinn, Manisha Senadeera, Stephan Jacobs, Simon Coghlan, Vuong Le
Trust and Medical AI: The challenges we face and the expertise needed to overcome them. CoRR (2020)
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
DeepCoDA: personalized interpretability for compositional health data. CoRR (2020)
Thomas P. Quinn, Stephan Jacobs, Manisha Senadeera, Vuong Le, Simon Coghlan
The Three Ghosts of Medical AI: Can the Black-Box Present Deliver? CoRR (2020)
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
DeepCoDA: personalized interpretability for compositional health data. ICML (2020)
Thomas P. Quinn
Visualizing balances of compositional data: A new alternative to balance dendrograms. F1000Research 7 (2018)
Thomas P. Quinn, Tamsyn M. Crowley, Mark F. Richardson
Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods. BMC Bioinform. 19 (1) (2018)
Thomas P. Quinn, Ionas Erb, Mark F. Richardson, Tamsyn M. Crowley
Understanding sequencing data as compositions: an outlook and review. Bioinform. 34 (16) (2018)
Thomas P. Quinn, Daniel Tylee, Stephen J. Glatt
exprso: an R-package for the rapid implementation of machine learning algorithms. F1000Research 5 (2016)