| Variability in the analysis of a single neuroimaging dataset by many teams R Botvinik-Nezer, F Holzmeister, CF Camerer, A Dreber, J Huber, ... Nature 582 (7810), 84-88, 2020 | 1019 | 2020 |
| Transfer function analysis of dynamic cerebral autoregulation: a white paper from the International Cerebral Autoregulation Research Network JAHR Claassen, ASS Meel-van den Abeelen, DM Simpson, RB Panerai, ... Journal of Cerebral Blood Flow & Metabolism 36 (4), 665-680, 2016 | 408 | 2016 |
| Determination of the human brainstem respiratory control network and its cortical connections in vivo using functional and structural imaging KTS Pattinson, GD Mitsis, AK Harvey, S Jbabdi, S Dirckx, SD Mayhew, ... Neuroimage 44 (2), 295-305, 2009 | 172 | 2009 |
| Nonlinear modeling of the dynamic effects of arterial pressure and CO/sub 2/variations on cerebral blood flow in healthy humans GD Mitsis, MJ Poulin, PA Robbins, VZ Marmarelis IEEE Transactions on Biomedical Engineering 51 (11), 1932-1943, 2004 | 155 | 2004 |
| Modeling of nonlinear physiological systems with fast and slow dynamics. II. Application to cerebral autoregulation GD Mitsis, R Zhang, BD Levine, VZ Marmarelis Annals of biomedical engineering 30, 555-565, 2002 | 131 | 2002 |
| Contextual bandits for adapting treatment in a mouse model of de novo carcinogenesis A Durand, C Achilleos, D Iacovides, K Strati, GD Mitsis, J Pineau Machine learning for healthcare conference, 67-82, 2018 | 127 | 2018 |
| Cerebral hemodynamics during orthostatic stress assessed by nonlinear modeling GD Mitsis, R Zhang, BD Levine, VZ Marmarelis Journal of Applied Physiology 101 (1), 354-366, 2006 | 93 | 2006 |
| Regions of interest analysis in pharmacological fMRI: how do the definition criteria influence the inferred result? GD Mitsis, GD Iannetti, TS Smart, I Tracey, RG Wise Neuroimage 40 (1), 121-132, 2008 | 91 | 2008 |
| Transfer function analysis of dynamic cerebral autoregulation: a CARNet white paper 2022 update RB Panerai, P Brassard, JS Burma, P Castro, JAHR Claassen, ... Journal of Cerebral Blood Flow & Metabolism 43 (1), 3-25, 2023 | 82 | 2023 |
| Between-centre variability in transfer function analysis, a widely used method for linear quantification of the dynamic pressure–flow relation: The CARNet study ASS Meel-van den Abeelen, DM Simpson, LJY Wang, CH Slump, ... Medical engineering & physics 36 (5), 620-627, 2014 | 79 | 2014 |
| Assessment of dynamic functional connectivity in resting‐state fMRI using the sliding window technique AD Savva, GD Mitsis, GK Matsopoulos Brain and behavior 9 (4), e01255, 2019 | 77 | 2019 |
| Modeling of nonlinear physiological systems with fast and slow dynamics. I. Methodology GD Mitsis, VZ Marmarelis Annals of biomedical engineering 30, 272-281, 2002 | 70 | 2002 |
| Mathematical modeling of tumor growth, drug-resistance, toxicity, and optimal therapy design M Hadjiandreou, GD Mitsis IEEE Transactions on Biomedical Engineering 61 (2), 415-425, 2014 | 61 | 2014 |
| Identification of physiological response functions to correct for fluctuations in resting-state fMRI related to heart rate and respiration M Kassinopoulos, GD Mitsis Neuroimage 202, 116150, 2019 | 55 | 2019 |
| Spontaneous physiological variability modulates dynamic functional connectivity in resting-state functional magnetic resonance imaging F Nikolaou, C Orphanidou, P Papakyriakou, K Murphy, RG Wise, ... Philosophical Transactions of the Royal Society A: Mathematical, Physical …, 2016 | 52 | 2016 |
| Classification and prediction of clinical improvement in deep brain stimulation from intraoperative microelectrode recordings K Kostoglou, KP Michmizos, P Stathis, D Sakas, KS Nikita, GD Mitsis IEEE Transactions on Biomedical Engineering 64 (5), 1123-1130, 2016 | 51 | 2016 |
| Autonomic neural control of cerebral hemodynamics GD Mitsis, R Zhang, BD Levine, E Tzanalaridou, DG Katritsis, ... IEEE engineering in medicine and biology magazine 28 (6), 54-62, 2009 | 51 | 2009 |
| Physiological and motion signatures in static and time-varying functional connectivity and their subject identifiability A Xifra-Porxas, M Kassinopoulos, GD Mitsis Elife 10, e62324, 2021 | 48* | 2021 |
| Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques A Xifra-Porxas, A Ghosh, GD Mitsis, MH Boudrias NeuroImage 231, 117822, 2021 | 48 | 2021 |
| Model-Based Tumor Growth Dynamics and Therapy Response in a Mouse Model of De Novo Carcinogenesis C Loizides, D Iacovides, MM Hadjiandreou, G Rizki, A Achilleos, K Strati, ... PloS one 10 (12), e0143840, 2015 | 43 | 2015 |
Kyriaki KostoglouDepartment of Electrical and Computer Engineering, McGill UniversityE-mail confirmado em mail.mcgill.ca
