| Brain tumour segmentation with incomplete imaging data JK Ruffle, S Mohinta, R Gray, H Hyare, P Nachev Brain Communications 5 (2), fcad118, 2023 | 6 | 2023 |
| Brain tumour genetic network signatures of survival JK Ruffle, S Mohinta, G Pombo, R Gray, V Kopanitsa, F Lee, S Brandner, ... Brain 146 (11), 4736-4754, 2023 | 4 | 2023 |
| Computational limits to the legibility of the imaged human brain JK Ruffle, RJ Gray, S Mohinta, G Pombo, C Kaul, H Hyare, G Rees, ... NeuroImage, 120600, 2024 | 1 | 2024 |
| DEMOGRAPHICS, GENETICS, AND EPIGENETICS INflUENCE THE LESION DISTRIBUTION OF GLIOMA J Ruffle, S Mohinta, S Brandner, H Hyare, P Nachev Neuro-Oncology 25 (Supplement_3), iii4-iii4, 2023 | | 2023 |
| BRAIN TUMOUR GENETIC NETWORK SIGNATURES SUPERIORLY FORECAST SURVIVAL J Ruffle, S Mohinta, G Pombo, R Gray, V Kopanitsa, F Lee, S Brandner, ... Neuro-Oncology 25 (Supplement_3), iii3-iii3, 2023 | | 2023 |
| The legibility of the imaged human brain JK Ruffle, RJ Gray, S Mohinta, G Pombo, C Kaul, H Hyare, G Rees, ... arXiv preprint arXiv:2309.07096, 2023 | | 2023 |
| Hippocampal networks support reinforcement learning in partially observable environments D Pedamonti, S Mohinta, M Dimitrov, H Malagon-Vina, S Ciocchi, ... bioRxiv, 2023.11. 09.565503, 2023 | | 2023 |
| Brain tumour segmentation with incomplete data J Ruffle, S Mohinta, R Gray, H Hyare, P Nachev | | 2022 |
| NIMG-35. THE DEEP TOPOLOGY OF GLIOMAS J Ruffle, S Mohinta, S Brandner, H Hyare, P Nachev Neuro-Oncology, 24 (Issue Supplement_7), vii171, 2022 | | 2022 |
| CNSC-26. NETWORK SIGNATURES OF SURVIVAL IN BRAIN TUMOUR GENETICS J Ruffle, S Mohinta, G Pombo, R Gray, V Kopanitsa, F Lee, S Brandner, ... Neuro-Oncology 24 (Suppl 7), vii27, 2022 | | 2022 |
| DEEP LEARNING FOR TUMOUR SEGMENTATION WITH MISSING DATA J Ruffle, S Mohinta, R Gray, H Hyare, P Nachev NEURO-ONCOLOGY 24, 16-16, 2022 | | 2022 |
| Identifying Enhancing Tumour Without Contrast-Enhanced Imaging J Ruffle, S Mohinta, R Gray, H Hyare, P Nachev Neuro-Oncology 24 (Supplement_4), iv3-iv3, 2022 | | 2022 |
| Hippocampal networks support continual learning and generalisation D Pedamonti*, S Mohinta*, M Dimitrov, H Malagon Vina, S Ciocchi, ... From Neuroscience to Artificially Intelligent Systems 'NAISYS', 2022 | | 2022 |
| Hippocampal networks support continual learning and generalisation S Mohinta*, D Pedamonti*, M Dimitrov, H Malagon Vina, S Ciocchi, ... Computational and Systems Neuroscience 'COSYNE', 2022 | | 2022 |
| Translating automated brain tumour phenotyping to clinical neuroimaging. JK Ruffle, S Mohinta, RJ Gray, H Hyare, P Nachev CoRR, 2022 | | 2022 |
| Hippocampal encoding of continual reinforcement learning features S Mohinta*, D Pedamonti*, M Dimitrov, H Malagon Vina, S Ciocchi, ... Computational and Systems Neuroscience 'COSYNE', 2021 | | 2021 |
| Hippocampal encoding of continual reinforcement learning features S Mohinta*, D Pedamonti*, M Dimitrov, H Malagon Vina, S Ciocchi, ... Advanced Course and Symposium on Artificial Intelligence & Neuroscience ‘ACAIN’, 2021 | | 2021 |
| Continual deep reinforcement learning in hippocampal networks S Mohinta*, D Pedamonti*, M Dimitrov, H Malagon Vina, S Ciocchi, ... Champalimaud Research Symposium, 2021 | | 2021 |
| Hippocampal population representations in reinforced continual learning S Mohinta, S Ciocchi, R Ponte Costa Computational and Systems Neuroscience 'COSYNE', 2020 | | 2020 |
| HIPPOCAMPAL NEURONAL REPRESENTATIONS IN CONTINUAL LEARNING S Mohinta, RP Costa, S Ciocchi | | 2019 |
Parashkev NachevUniversity College LondonVerified email at ucl.ac.uk
