| Machine learning in deep brain stimulation: A systematic review M Peralta, P Jannin, JSH Baxter Artificial Intelligence in Medicine 122, 102198, 2021 | 16 | 2021 |
| Data imputation and compression for Parkinson's disease clinical questionnaires M Peralta, P Jannin, C Haegelen, JSH Baxter Artificial Intelligence in Medicine 114, 102051, 2021 | 15 | 2021 |
| Extending convolutional neural networks for localizing the subthalamic nucleus from micro-electrode recordings in Parkinson’s disease T Martin, M Peralta, G Gilmore, P Sauleau, C Haegelen, P Jannin, ... Biomedical Signal Processing and Control 67, 102529, 2021 | 11 | 2021 |
| Striatal shape alteration as a staging biomarker for Parkinson’s Disease M Peralta, JSH Baxter, AR Khan, C Haegelen, P Jannin NeuroImage: Clinical 27, 102272, 2020 | 7 | 2020 |
| PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes M Peralta, C Haegelen, P Jannin, JSH Baxter International Journal of Computer Assisted Radiology and Surgery 16 (8 …, 2021 | 6 | 2021 |
| Sepaconvnet for localizing the subthalamic nucleus using one second micro-electrode recordings M Peralta, QA Bui, A Ackaouy, T Martin, G Gilmore, C Haegelen, ... 2020 42nd Annual International Conference of the IEEE Engineering in …, 2020 | 5 | 2020 |
| Data driven methods to support decision making in Deep Brain Stimulation for Parkinson’s disease M Péralta Université Rennes 1, 2020 | | 2020 |
| Does introduction of priors improve reliability to segment hyperdirect connections using tractography for Deep Brain Stimulation? T MOREAU, M PERALTA, J BAXTER, P JANNIN | | |
Pierre JanninMediCIS, LTSI, Inserm, Université de RennesVerified email at univ-rennes1.fr
