2024
Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER. (Conference Paper)
Abaho, M., Bollegala, D., Leeming, G., Joyce, D., & Buchan, I. E. (2024). Improving Pre-trained Language Model Sensitivity via Mask Specific losses: A case study on Biomedical NER.. In CoRR Vol. abs/2403.18025.
Joyce, D. W., Kormilitzin, A., Hamer-Hunt, J., McKee, K. R., & Tomasev, N. (2024). Defining acceptable data collection and reuse standards for queer artificial intelligence research in mental health: protocol for the online PARQAIR-MH Delphi study.. BMJ open, 14(3), e079105. doi:10.1136/bmjopen-2023-079105DOI: 10.1136/bmjopen-2023-079105
Woodall, A. A., Abuzour, A. S., Wilson, S. A., Mair, F. S., Buchan, I., Sheard, S. B., . . . Walker, L. E. (2024). Management of antipsychotics in primary care: Insights from healthcare professionals and policy makers in the United Kingdom.. PloS one, 19(3), e0294974. doi:10.1371/journal.pone.0294974DOI: 10.1371/journal.pone.0294974
2023
Taylor, N., Zhang, Y., Joyce, D. W., Gao, Z., Kormilitzin, A., & Nevado-Holgado, A. (2023). Clinical Prompt Learning With Frozen Language Models. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. doi:10.1109/TNNLS.2023.3294633DOI: 10.1109/TNNLS.2023.3294633
Drousiotis, E., Joyce, D. W., Dempsey, R. C., Haines, A., Spirakis, P. G., Shi, L., & Maskell, S. (2023). Probabilistic Decision Trees for Predicting 12-Month University Students Likely to Experience Suicidal Ideation. In Unknown Conference (pp. 475-487). Springer Nature Switzerland. doi:10.1007/978-3-031-34111-3_40DOI: 10.1007/978-3-031-34111-3_40
Joyce, D. W., Kormilitzin, A., Smith, K. A., & Cipriani, A. (2023). Explainable artificial intelligence for mental health through transparency and interpretability for understandability. NPJ DIGITAL MEDICINE, 6(1). doi:10.1038/s41746-023-00751-9DOI: 10.1038/s41746-023-00751-9
Mannan, F. A., Porffy, L. A., Joyce, D. W., Shergill, S. S., & Celiktutan, O. (2023). Automatic Detection of Cognitive Impairment with Virtual Reality. SENSORS, 23(2). doi:10.3390/s23021026DOI: 10.3390/s23021026
A participatory initiative to include LGBT plus voices in AI for mental health (Journal article)
Kormilitzin, A., Tomasev, N., McKee, K. R., & Joyce, D. W. (2023). A participatory initiative to include LGBT plus voices in AI for mental health. NATURE MEDICINE, 29(1), 10-11. doi:10.1038/s41591-022-02137-yDOI: 10.1038/s41591-022-02137-y
2022
Bolton, S., Joyce, D. W., Gordon-Smith, K., Jones, L., Jones, I., Geddes, J., & Saunders, K. E. A. (2022). Psychosocial markers of age at onset in bipolar disorder: a machine learning approach.. BJPsych open, 8(4), e133. doi:10.1192/bjo.2022.536DOI: 10.1192/bjo.2022.536
2018
Capturing Rest-Activity Profiles in Schizophrenia Using Wearable and Mobile Technologies: Development, Implementation, Feasibility, and Acceptability of a Remote Monitoring Platform. (Journal article)
Meyer, N., Kerz, M., Folarin, A., Joyce, D. W., Jackson, R., Karr, C., . . . MacCabe, J. (2018). Capturing Rest-Activity Profiles in Schizophrenia Using Wearable and Mobile Technologies: Development, Implementation, Feasibility, and Acceptability of a Remote Monitoring Platform.. JMIR mHealth and uHealth, 6(10), e188. doi:10.2196/mhealth.8292DOI: 10.2196/mhealth.8292
