| Mathematical Model-Driven Deep Learning Enables Personalized Adaptive Therapy K Gallagher, MAR Strobl, DS Park, FC Spoendlin, RA Gatenby, PK Maini, ... Cancer Research 84 (11), 1929-1941, 2024 | 5 | 2024 |
| Epidemiological Agent-Based Modelling Software (Epiabm) K Gallagher, I Bouros, N Fan, E Hayman, L Heirene, P Lamirande, ... Journal of Open Research Software 12 (1), 3, 2024 | 4 | 2024 |
| Identification and attribution of weekly periodic biases in epidemiological time series data K Gallagher, R Creswell, D Gavaghan, B Lambert medRxiv, 2023.06. 13.23290903, 2023 | 2 | 2023 |
| EpiGeoPop: A Tool for Developing Spatially Accurate Country-level Epidemiological Models L Herriott, HL Capel, I Ellmen, N Schofield, J Zhu, B Lambert, D Gavaghan, ... arXiv preprint arXiv:2310.13468, 2023 | 1 | 2023 |
| Ten simple rules for training scientists to make better software K Gallagher, R Creswell, B Lambert, M Robinson, C Lok Lei, GR Mirams, ... PLOS Computational Biology 20 (9), e1012410, 2024 | | 2024 |
| Learning to Adapt-Personalizing Adaptive Therapy Schedules using Deep Reinforcement Learning K Gallagher The Mathematical Oncology Blog, 2024 | | 2024 |
| Abstract PR001: Learning to adapt: Rational personalization of adaptive therapy using deep reinforcement learning K Gallagher, M Strobl, R Gatenby, P Maini, A Anderson Cancer Research 84 (3_Supplement_2), PR001-PR001, 2024 | | 2024 |
| Toward new liquid crystal phases of DNA mesogens K Gallagher, J Yu, DA King, R Liu, E Eiser APL Materials 11 (6), 061129, 2023 | | 2023 |
| Learning to Adapt-Deep Reinforcement Learning in Treatment-Resistant Prostate Cancer K Gallagher, M Strobl, R Gatenby, P Maini, A Anderson bioRxiv, 2023.04. 28.538766, 2023 | | 2023 |
| Adaptive treatment scheduling of PARP inhibitors in ovarian cancer: Using mathematical modeling to assess clinical feasibility and estimate potential benefits MA Strobl, AL Martin, C Gallagher, M Damaghi, M Robertson-Tessi, ... Cancer Research 83 (7_Supplement), 5694-5694, 2023 | | 2023 |
David GavaghanProfessor of Computational Biology, University of Oxford在 cs.ox.ac.uk 的电子邮件经过验证
