| Clinically Applicable Deep Learning for Diagnosis and Referral in Retinal Disease J Defauw, J Ledsam, Romera-Paredes B., N S., T Nenad, B S., A H., ... Nature Medicine, 2018 | 889 | 2018 |
| A clinically applicable approach to continuous prediction of future acute kidney injury Nature 572 (7767), 116-119, 2019 | 259 | 2019 |
| The role of hubness in clustering high-dimensional data N Tomasev, M Radovanovic, D Mladenic, M Ivanovic IEEE transactions on knowledge and data engineering 26 (3), 739-751, 2013 | 178 | 2013 |
| Hubness-based fuzzy measures for high-dimensional k-nearest neighbor classification N Tomašev, M Radovanović, D Mladenić, M Ivanović International Journal of Machine Learning and Cybernetics 5 (3), 445-458, 2014 | 77 | 2014 |
| A probabilistic approach to nearest-neighbor classification: naive hubness bayesian kNN N Tomasev, M Radovanović, D Mladenić, M Ivanović Proceedings of the 20th ACM international conference on Information and …, 2011 | 69 | 2011 |
| Nearest neighbor voting in high-dimensional data: Learning from past occurrences N Tomasev, D Mladenic 2011 IEEE 11th International Conference on Data Mining Workshops, 1215-1218, 2011 | 65 | 2011 |
| The role of hubness in clustering high-dimensional data N Tomašev, M Radovanović, D Mladenić, M Ivanović Pacific-Asia Conference on Knowledge Discovery and Data Mining, 183-195, 2011 | 63 | 2011 |
| Class imbalance and the curse of minority hubs N Tomašev, D Mladenić Knowledge-Based Systems 53, 157-172, 2013 | 51 | 2013 |
| Hubness-aware shared neighbor distances for high-dimensional -nearest neighbor classification N Tomašev, D Mladenić Knowledge and information systems 39 (1), 89-122, 2014 | 49 | 2014 |
| Hubness-based fuzzy measures for high-dimensional k-nearest neighbor classification N Tomašev, M Radovanović, D Mladenić, M Ivanović International Journal of Machine Learning and Cybernetics 5 (3), 445-458, 2014 | 48 | 2014 |
| Hubness-aware classification, instance selection and feature construction: Survey and extensions to time-series N Tomašev, K Buza, K Marussy, PB Kis Feature selection for data and pattern recognition, 231-262, 2015 | 42 | 2015 |
| Automated analysis of retinal imaging using machine learning techniques for computer vision JC Jeffrey De Fauw, Pearse Keane1, Nenad Tomasev, Daniel Visentin, George ... F1000Research, 2016 | 41 | 2016 |
| The influence of hubness on nearest-neighbor methods in object recognition N Tomašev, R Brehar, D Mladenić, S Nedevschi 2011 IEEE 7th International Conference on Intelligent Computer Communication …, 2011 | 35 | 2011 |
| Hubness-aware kNN classification of high-dimensional data in presence of label noise N Tomašev, K Buza Neurocomputing 160, 157-172, 2015 | 31 | 2015 |
| Hub Co-occurrence Modeling for Robust High-Dimensional kNN Classification N Tomašev, D Mladenić Joint European Conference on Machine Learning and Knowledge Discovery in …, 2013 | 29 | 2013 |
| Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans JC Carlton Chu, Jeffrey De Fauw, Nenad Tomasev, Bernardino Romera Paredes ... F1000Research 5, 2016 | 21 | 2016 |
| A case for hubness removal in high–dimensional multimedia retrieval D Schnitzer, A Flexer, N Tomašev European conference on information retrieval, 687-692, 2014 | 21 | 2014 |
| Hubness-based clustering of high-dimensional data N Tomašev, M Radovanović, D Mladenić, M Ivanović Partitional clustering algorithms, 353-386, 2015 | 19 | 2015 |
| Clustering evaluation in high-dimensional data N Tomašev, M Radovanović Unsupervised Learning Algorithms, 71-107, 2016 | 16 | 2016 |
| Choosing the Metric in High-Dimensional Spaces Based on Hub Analysis. D Schnitzer, A Flexer, N Tomasev ESANN, 2014 | 15 | 2014 |
Dunja MladenicSenior researcher at J. Stefan InstituteVerified email at ijs.si
