Professor Paul Bonnington
Professor

Paul Bonnington

Email: 
Phone: 
+61 7 336 53609

Availability

Professor Paul Bonnington is:
Not available for supervision

Search Professor Paul Bonnington’s works on UQ eSpace

4 works between 2014 and 2025
All (4) Journal Article (2) Conference Publication (2)

1 - 4 of 4 works

2025

Journal Article

Multi‐task <scp>AI</scp> models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis

Mehta, Deval, Primiero, Clare, Betz‐Stablein, Brigid, Nguyen, Toan D., Gal, Yaniv, Bowling, Adrian, Haskett, Martin, Sashindranath, Maithili, Bonnington, Paul, Mar, Victoria, Soyer, H. Peter and Ge, Zongyuan (2025). Multi‐task AI models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis. Journal of the European Academy of Dermatology and Venereology. doi: 10.1111/jdv.20551

Multi‐task <scp>AI</scp> models in dermatology: Overcoming critical clinical translation challenges for enhanced skin lesion diagnosis

2022

Conference Publication

Skin lesion recognition with class-hierarchy regularized hyperbolic embeddings

Yu, Zhen, Nguyen, Toan, Gal, Yaniv, Ju, Lie, Chandra, Shekhar S., Zhang, Lei, Bonnington, Paul, Mar, Victoria, Wang, Zhiyong and Ge, Zongyuan (2022). Skin lesion recognition with class-hierarchy regularized hyperbolic embeddings. 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Singapore, Singapore, 18-22 September 2022. Heidelberg, Germany: Springer. doi: 10.1007/978-3-031-16437-8_57

Skin lesion recognition with class-hierarchy regularized hyperbolic embeddings

2021

Conference Publication

End-to-end ugly duckling sign detection for melanoma identification with transformers

Yu, Zhen, Mar, Victoria, Eriksson, Anders, Chandra, Shakes, Bonnington, Paul, Zhang, Lei and Ge, Zongyuan (2021). End-to-end ugly duckling sign detection for melanoma identification with transformers. Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, Strasbourg, France, 27 September-1 October 2021. Cham, Switzerland: Springer Nature Switzerland. doi: 10.1007/978-3-030-87234-2_17

End-to-end ugly duckling sign detection for melanoma identification with transformers

2014

Journal Article

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

Goscinski, Wojtek J., McIntosh, Paul, Felzmann, Ulrich, Maksimenko, Anton, Hall, Christopher J., Gureyev, Timur, Thompson, Darren, Janke, Andrew, Galloway, Graham, Killeen, Neil E. B., Raniga, Parnesh, Kaluza, Owen, Ng, Amanda, Poudel, Govinda, Barnes, David G., Nguyen, Toan, Bonnington, Paul and Egan, Gary F. (2014). The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research. Frontiers in Neuroinformatics, 8 (30) 30, 1-13. doi: 10.3389/fninf.2014.00030

The multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research

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