Thomas P. Quinn

21 papers A* 2Journal 19
YearRankTypeTitle / Venue / Authors
2024 J jnl
Ethics of using artificial intelligence (AI) in veterinary medicine.
AI Soc.
Simon Coghlan, Thomas P. Quinn
2023 J jnl
Explaining Black Box Drug Target Prediction Through Model Agnostic Counterfactual Samples.
IEEE ACM Trans. Comput. Biol. Bioinform.
Tri Minh Nguyen, Thomas P. Quinn, Thin Nguyen, Truyen Tran
2022 A* conf
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome.
NeurIPS
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
2022 J jnl
Data Augmentation for Compositional Data: Advancing Predictive Models of the Microbiome.
CoRR
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
2022 J jnl
The three ghosts of medical AI: Can the black-box present deliver?
Artif. Intell. Medicine
Thomas P. Quinn, Stephan Jacobs, Manisha Senadeera, Vuong Le, Simon Coghlan
2021 J jnl
A Field Guide to Scientific XAI: Transparent and Interpretable Deep Learning for Bioinformatics Research.
CoRR
Thomas P. Quinn, Sunil Gupta, Svetha Venkatesh, Vuong Le
2021 J jnl
Counterfactual Explanation with Multi-Agent Reinforcement Learning for Drug Target Prediction.
CoRR
Tri Minh Nguyen, Thomas P. Quinn, Thin Nguyen, Truyen Tran
2021 J jnl
GraphDTA: predicting drug-target binding affinity with graph neural networks.
Bioinform.
Thin Nguyen, Hang Le, Thomas P. Quinn, Tri Nguyen, Thuc Duy Le, Svetha Venkatesh
2021 J jnl
Learning sparse log-ratios for high-throughput sequencing data.
Bioinform.
Elliott Gordon-Rodríguez, Thomas P. Quinn, John P. Cunningham
2021 J jnl
PAN: Personalized Annotation-Based Networks for the Prediction of Breast Cancer Relapse.
IEEE ACM Trans. Comput. Biol. Bioinform.
Thin Nguyen, Samuel C. Lee, Thomas P. Quinn, Buu Minh Thanh Truong, Xiaomei Li, Truyen Tran, Svetha Venkatesh, Thuc Duy Le
2021 J jnl
Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient.
BioData Min.
Haripriya Harikumar, Thomas P. Quinn, Santu Rana, Sunil Gupta, Svetha Venkatesh
2021 J jnl
Readying Medical Students for Medical AI: The Need to Embed AI Ethics Education.
CoRR
Thomas P. Quinn, Simon Coghlan
2021 J jnl
Trust and medical AI: the challenges we face and the expertise needed to overcome them.
J. Am. Medical Informatics Assoc.
Thomas P. Quinn, Manisha Senadeera, Stephan Jacobs, Simon Coghlan, Vuong Le
2020 A* conf
DeepCoDA: personalized interpretability for compositional health data.
ICML
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020 J jnl
DeepCoDA: personalized interpretability for compositional health data.
CoRR
Thomas P. Quinn, Dang Nguyen, Santu Rana, Sunil Gupta, Svetha Venkatesh
2020 J jnl
The Three Ghosts of Medical AI: Can the Black-Box Present Deliver?
CoRR
Thomas P. Quinn, Stephan Jacobs, Manisha Senadeera, Vuong Le, Simon Coghlan
2020 J jnl
Trust and Medical AI: The challenges we face and the expertise needed to overcome them.
CoRR
Thomas P. Quinn, Manisha Senadeera, Stephan Jacobs, Simon Coghlan, Vuong Le
2018 J jnl
Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods.
BMC Bioinform.
Thomas P. Quinn, Tamsyn M. Crowley, Mark F. Richardson
2018 J jnl
Understanding sequencing data as compositions: an outlook and review.
Bioinform.
Thomas P. Quinn, Ionas Erb, Mark F. Richardson, Tamsyn M. Crowley
2018 J jnl
Visualizing balances of compositional data: A new alternative to balance dendrograms.
F1000Research
Thomas P. Quinn
2016 J jnl
exprso: an R-package for the rapid implementation of machine learning algorithms.
F1000Research
Thomas P. Quinn, Daniel Tylee, Stephen J. Glatt