| Supervised fuzzy partitioning P Ashtari, FN Haredasht, H Beigy Pattern Recognition 97, 107013, 2020 | 11 | 2020 |
| Comparison between cystatin C-and creatinine-based estimated glomerular filtration rate in the follow-up of patients recovering from a stage-3 AKI in ICU F Nateghi Haredasht, L Viaene, C Vens, N Callewaert, W De Corte, ... Journal of clinical medicine 11 (24), 7264, 2022 | 5 | 2022 |
| The effect of different consensus definitions on diagnosing acute kidney injury events and their association with in-hospital mortality F Nateghi Haredasht, M Antonatou, E Cavalier, P Delanaye, H Pottel, ... Journal of Nephrology 35 (8), 2087-2095, 2022 | 5 | 2022 |
| Predicting outcomes of acute kidney injury in critically ill patients using machine learning F Nateghi Haredasht, L Viaene, H Pottel, W De Corte, C Vens Scientific Reports 13 (1), 9864, 2023 | 4 | 2023 |
| Predicting survival outcomes in the presence of unlabeled data F Nateghi Haredasht, C Vens Machine Learning 111 (11), 4139-4157, 2022 | 4 | 2022 |
| Validated risk prediction models for outcomes of acute kidney injury: a systematic review FN Haredasht, L Vanhoutte, C Vens, H Pottel, L Viaene, W De Corte BMC nephrology 24 (1), 133, 2023 | 2 | 2023 |
| Exploiting censored information in self-training for time-to-event prediction FN Haredasht, KA Dauda, C Vens Ieee Access, 2023 | 1 | 2023 |
| Exploiting unlabeled data to predict the development of CKD after AKI in critically ill patients F Nateghi Haredasht, L Viaene, W De Corte, C Vens Intelligence Artificielle & Néphrologie 2021, Date: 2021/02/11-2021/02/12 …, 2021 | 1 | 2021 |
| Causal inference of gene expression data using a clustering-based extension of kernel-granger causality FN Haredasht, F Ghassemi, MH Moradi 2016 23rd Iranian Conference on Biomedical Engineering and 2016 1st …, 2016 | 1 | 2016 |
| Estimation of GFR with machine learning models compared to EKFC equation FK Nakano, A Lanot, A Akesson, H Pottel, P Delanaye, U Nyman, J Bjork, ... 2ème Conferénce Intelligence Artificielle Néphrologie, Date: 2023/09/14-2023 …, 2023 | | 2023 |
| Development of predictive models for critically ill patients with acute kidney injury F Nateghi Haredasht | | 2023 |
| Serum Creatinine‑based versus Cystatin C‑based eGFR in AKI-stage3 critically ill patients F Nateghi Haredasht, L Viaene, C Vens, W De Corte, H Pottel ESICM–European society of intensive medicine, Date: 2022/05/12-2022/05/14 …, 2022 | | 2022 |
| Nonlinear Causality Inference in Microarray Time Series. FN Haredasht, MH Moradi BNAIC/BENELEARN, 2019 | | 2019 |
| Machine learning tools provide insight in the initiation and outcome of renal replacement C Vens, MD Wouter De Corte, MD Sven Van Poucke, H Van Overmeire | | |
Celine Vensprofessor, Katholieke Universiteit LeuvenVerified email at kuleuven.be
