| Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open … J Guinney, T Wang, TD Laajala, KK Winner, JC Bare, EC Neto, SA Khan, ... The Lancet Oncology 18 (1), 132-142, 2017 | 160 | 2017 |
| Retinal vessel extraction using lattice neural networks with dendritic processing R Vega, G Sanchez-Ante, LE Falcon-Morales, H Sossa, E Guevara Computers in biology and medicine 58, 20-30, 2015 | 156 | 2015 |
| SIMLR: Machine Learning inside the SIR model for COVID-19 Forecasting R Vega, L Flores, R Greiner Forecasting 4 (1), 72-94, 2022 | 31 | 2022 |
| Skill learning from kinesthetic feedback D Pinzon, R Vega, YP Sanchez, B Zheng The American Journal of Surgery 214 (4), 721-725, 2017 | 29 | 2017 |
| Assessment of feature selection and classification methods for recognizing motor imagery tasks from electroencephalographic signals. R Vega, T Sajed, KW Mathewson, K Khare, PM Pilarski, R Greiner, ... Artif. Intell. Res. 6 (1), 37-51, 2017 | 29 | 2017 |
| Accurate long-range forecasting of COVID-19 mortality in the USA P Ramazi, A Haratian, M Meghdadi, A Mari Oriyad, MA Lewis, Z Maleki, ... Scientific reports 11 (1), 13822, 2021 | 24 | 2021 |
| Neurocognitive graphs of first-episode schizophrenia and major depression based on cognitive features S Liang, R Vega, X Kong, W Deng, Q Wang, X Ma, M Li, X Hu, ... Neuroscience bulletin 34, 312-320, 2018 | 23 | 2018 |
| A DREAM challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer F Seyednasrollah, DC Koestler, T Wang, SR Piccolo, R Vega, R Greiner, ... JCO clinical cancer informatics 1, 1-15, 2017 | 19 | 2017 |
| Blood vessel segmentation in retinal images using lattice neural networks R Vega, E Guevara, LE Falcon, G Sanchez-Ante, H Sossa Advances in Artificial Intelligence and Its Applications: 12th Mexican …, 2013 | 19 | 2013 |
| Improving pattern classification of DNA microarray data by using PCA and logistic regression R Ocampo-Vega, G Sanchez-Ante, MA de Luna, R Vega, ... Intelligent Data Analysis 20 (s1), S53-S67, 2016 | 18 | 2016 |
| Empiric neurocognitive performance profile discovery and interpretation in HIV infection D Gomez, C Power, MJ Gill, N Koenig, R Vega, E Fujiwara Journal of NeuroVirology 25, 72-84, 2019 | 16 | 2019 |
| Hemodynamic pattern recognition during deception process using functional near-infrared spectroscopy R Vega, AG Hernandez-Reynoso, EK Linn, RQ Fuentes-Aguilar, ... Journal of Medical and Biological Engineering 36, 22-31, 2016 | 12 | 2016 |
| Classification of hand movements from non-invasive brain signals using lattice neural networks with dendritic processing L Ojeda, R Vega, LE Falcon, G Sanchez-Ante, H Sossa, JM Antelis Pattern Recognition: 7th Mexican Conference, MCPR 2015, Mexico City, Mexico …, 2015 | 11 | 2015 |
| Thyroid nodule segmentation and classification using deep convolutional neural network and rule-based classifiers A Shahroudnejad, R Vega, A Forouzandeh, S Balachandran, J Jaremko, ... 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 10 | 2021 |
| Sample efficient learning of image-based diagnostic classifiers via probabilistic labels R Vega, P Gorji, Z Zhang, X Qin, AR Hareendranathan, J Kapur, ... International Conference on Artificial Intelligence and Statistics, 739-747, 2021 | 8 | 2021 |
| Finding effective ways to (machine) learn fmri-based classifiers from multi-site data R Vega, R Greiner International Workshop on Machine Learning in Clinical Neuroimaging, 32-39, 2018 | 6 | 2018 |
| Integrating user-input into deep convolutional neural networks for thyroid nodule segmentation R Daulatabad, R Vega, JL Jaremko, J Kapur, AR Hareendranathan, ... 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 5 | 2021 |
| Pattern analysis in DNA microarray data through PCA-based gene selection R Ocampo, MA de Luna, R Vega, G Sanchez-Ante, LE Falcon-Morales, ... Progress in Pattern Recognition, Image Analysis, Computer Vision, and …, 2014 | 5 | 2014 |
| Semi-counterfactual risk minimization via neural networks G Aminian, R Vega, O Rivasplata, L Toni, M Rodrigues arXiv preprint arXiv:2209.07148, 2022 | 1 | 2022 |
| Domain-shift adaptation via linear transformations R Vega, R Greiner arXiv preprint arXiv:2201.05282, 2022 | 1 | 2022 |
Gildardo Sanchez-Ante (0000-0003-3...Professor of Computer Science, Tecnologico de Monterrey在 tec.mx 的电子邮件经过验证
