Mr David Owen

2025

• McNabb, C. B. et al. 2025. WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis. Scientific Data 12, article number: 220. (10.1038/s41597-024-04154-7)

2024

• Owen, D., Lynham, A. J., Smart, S. E., Pardiñas, A. F. and Camacho Collados, J. 2024. AI for analyzing mental health disorders among social media users: Quarter-century narrative review of progress and challenges. Journal of Medical Internet Research 26, article number: e59225. (10.2196/59225)

2023

• Owen, D., Antypas, D., Hassoulas, A., Pardinas, A., Espinosa-Anke, L. and Camacho Collados, J. 2023. Enabling early health care intervention by detecting depression in users of web-based forums using Language models: longitudinal analysis and evaluation. JMIR AI 2, article number: e41205. (10.2196/41205)

2021

• Koller, K. et al. 2021. MICRA: Microstructural Image Compilation with Repeated Acquisitions. NeuroImage 225, article number: 117406. (10.1016/j.neuroimage.2020.117406)

2020

• Owen, D., Camacho Collados, J. and Espinosa-Anke, L. 2020. Towards preemptive detection of depression and anxiety in Twitter. Presented at: Social Media Mining for Health Applications Workshop & Shared Task 2020, Barcelona, Spain, 8-13 December 2020 Presented at Gonzalez-Hernandez, G. et al. eds.Proceedings of the Fifth Social Media Mining for Health Applications Workshop & Shared Task. Association for Computational Linguistics pp. 82-89.
• Owen, D. et al. 2020. Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections.[Version 2]. Research Ideas and Outcomes 6, article number: e58030. (10.3897/rio.6.e58030)
• Owen, D. et al. 2020. Towards a scientific workflow featuring Natural Language Processing for the digitisation of natural history collections [Version 1]. Research Ideas and Outcomes 6, article number: e55789. (10.3897/rio.6.e55789)
• Button, K., Spasic, I., Playle, R., Owen, D., Lau, M., Hannaway, L. and Jones, S. 2020. Using routine referral data for patients with knee and hip pain to improve access to specialist care. BMC Musculoskeletal Disorders 21, article number: 66. (10.1186/s12891-020-3087-x)

2019

• Spasic, I., Owen, D., Smith, A. and Button, K. 2019. KLOSURE: Closing in on open–ended patient questionnaires with text mining. Journal of Biomedical Semantics 10(S1), article number: 24. (10.1186/s13326-019-0215-3)
• Spasic, I., Owen, D., Knight, D. and Artemiou, A. 2019. Unsupervised multi-word term recognition in Welsh. Presented at: Celtic Language Technology Workshop 2019, Dublin, Ireland, 19 August 2019 Presented at Lynn, T. et al. eds.Proceedings of the Celtic Language Technology Workshop. European Association for Machine Translation
• Nieva De La Hidalga, A., Owen, D., Spasic, I., Rosin, P. and Sun, X. 2019. Use of semantic segmentation for increasing the throughput of digitisation workflows for natural history collections. Presented at: Biodiversity_Next 2019, Leiden, The Netherlands, 21-25 October 2019Biodiversity Information Science and Standards, Vol. 3. Vol. e37161. Pensoft, (10.3897/biss.3.37161)

2018

• Spasic, I., Owen, D., Smith, A. and Button, K. 2018. Closing in on open-ended patient questionnaires with text mining. Presented at: UK Healthcare Text Analytics Conference (HealTAC), Manchester, UK, 18-19 April 2018.
• Button, K., Owen, D., Lau, T., Spasic, I., Playle, R., Hannaway, L. and Jones, S. 2018. Improving access to care and treatment for patients with hip and knee pain at the interface between primary and secondary care. Presented at: OARSI 2018 World Congress on Osteoarthritis, Liverpool, UK, 26-29 April 2018.