| The use of the area under the ROC curve in the evaluation of machine learning algorithms AP Bradley Pattern recognition 30 (7), 1145-1159, 1997 | 8950 | 1997 |
| Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS … MJ Cardoso, T Arbel, G Carneiro, T Syeda-Mahmood, JMRS Tavares, ... Springer, 2017 | 795 | 2017 |
| Deep learning in cancer diagnosis, prognosis and treatment selection KA Tran, O Kondrashova, A Bradley, ED Williams, JV Pearson, N Waddell Genome Medicine 13, 1-17, 2021 | 614 | 2021 |
| Perceptual quality metrics applied to still image compression MP Eckert, AP Bradley Signal processing 70 (3), 177-200, 1998 | 488 | 1998 |
| Intelligible support vector machines for diagnosis of diabetes mellitus N Barakat, AP Bradley, MNH Barakat IEEE transactions on information technology in biomedicine 14 (4), 1114-1120, 2010 | 486 | 2010 |
| A deep learning approach for the analysis of masses in mammograms with minimal user intervention N Dhungel, G Carneiro, AP Bradley Medical image analysis 37, 114-128, 2017 | 393 | 2017 |
| Why rankings of biomedical image analysis competitions should be interpreted with care L Maier-Hein, M Eisenmann, A Reinke, S Onogur, M Stankovic, P Scholz, ... Nature communications 9 (1), 5217, 2018 | 363 | 2018 |
| Unregistered multiview mammogram analysis with pre-trained deep learning models G Carneiro, J Nascimento, AP Bradley International conference on medical image computing and computer-assisted …, 2015 | 359 | 2015 |
| Automated mass detection in mammograms using cascaded deep learning and random forests N Dhungel, G Carneiro, AP Bradley 2015 international conference on digital image computing: techniques and …, 2015 | 303 | 2015 |
| Face detection in digital images E Ho, AJ Lennon, AP Bradley US Patent 6,661,907, 2003 | 276* | 2003 |
| Rule extraction from support vector machines: a review N Barakat, AP Bradley Neurocomputing 74 (1-3), 178-190, 2010 | 275 | 2010 |
| An improved joint optimization of multiple level set functions for the segmentation of overlapping cervical cells Z Lu, G Carneiro, AP Bradley IEEE transactions on image processing 24 (4), 1261-1272, 2015 | 270 | 2015 |
| A wavelet visible difference predictor AP Bradley IEEE Transactions on image processing 8 (5), 717-730, 1999 | 245 | 1999 |
| Automated analysis of unregistered multi-view mammograms with deep learning G Carneiro, J Nascimento, AP Bradley IEEE transactions on medical imaging 36 (11), 2355-2365, 2017 | 224 | 2017 |
| Deep learning and structured prediction for the segmentation of mass in mammograms N Dhungel, G Carneiro, AP Bradley International Conference on Medical image computing and computer-assisted …, 2015 | 212 | 2015 |
| Precision radiology: predicting longevity using feature engineering and deep learning methods in a radiomics framework L Oakden-Rayner, G Carneiro, T Bessen, JC Nascimento, AP Bradley, ... Scientific reports 7 (1), 1648, 2017 | 185 | 2017 |
| Evaluation of three algorithms for the segmentation of overlapping cervical cells Z Lu, G Carneiro, AP Bradley, D Ushizima, MS Nosrati, AGC Bianchi, ... IEEE journal of biomedical and health informatics 21 (2), 441-450, 2016 | 178 | 2016 |
| Shift-invariance in the discrete wavelet transform AP Bradley Proceedings of VIIth Digital Image Computing: Techniques and Applications …, 2003 | 177 | 2003 |
| The automated learning of deep features for breast mass classification from mammograms N Dhungel, G Carneiro, AP Bradley Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 176 | 2016 |
| Rule extraction from support vector machines: A sequential covering approach NH Barakat, AP Bradley IEEE Transactions on Knowledge and Data Engineering 19 (6), 729-741, 2007 | 145 | 2007 |
Gustavo CarneiroProfessor of AI and Machine Learning, University of Surreysurrey.ac.uk의 이메일 확인됨