Abstract Background Donepezil, galantamine, rivastigmine and memantine are potentially effective interventions for cognitive impairment in dementia, but the use of these drugs has not been personalised to individual patients yet. We examined whether artificial intelligence-based recommendations can identify the best…
BACKGROUND Antipsychotic medications such as risperidone, olanzapine and aripiprazole are used to treat psychological and behavioural symptoms among dementia patients. Current evidence indicate prescription rates for antipsychotics vary and wider consensus to evaluate clinical epidemiological outcomes is limited. AIM…
Highlights Linking UK Clinical Record Interactive Search (UK-CRIS) and UK Biobank. Comparison of diagnosis for 854 individuals present in both datasets. Electronic health records from UK-CRIS used to understand self-reported data in UK Biobank. Abstract UK Biobank (UKB) is widely…
Overview A project between Oxford Health NHS Foundation Trust, Southern Health NHS Foundation Trust, the University of Oxford and Akrivia Health. The aim is to investigate the impact of the COVID pandemic on mental health services. We look at the…
Abstract In this work, we addressed the problem of capturing sequential information contained in longitudinal electronic health records (EHRs). Clinical notes, which is a particular type of EHR data, are a rich source of information and practitioners often develop clever…
Abstract Background The efficacy of acetylcholinesterase inhibitors and memantine in the symptomatic treatment of Alzheimer’s disease is well-established. Randomised trials have shown them to be associated with a reduction in the rate of cognitive decline. Aims To investigate the real-world…
Abstract The field of clinical natural language processing has been advanced significantly since the introduction of deep learning models. The self-supervised representation learning and the transfer learning paradigm became the methods of choice in many natural language processing application, in…
Background Utilisation of routinely collected electronic health records from secondary care offers unprecedented possibilities for medical science research but can also present difficulties. One key issue is that medical information is presented as free-form text and, therefore, requires time commitment…
Abstract Background: Antipsychotic prescription in older people with mental health problems can have severe adverse effects such as an increased risk of falls and show higher mortality rates. Moreover, this risk is elevated for the elderly with dementia. Aims: To…
Abstract Neural networks (NNs) have become the state of the art in many machine learning applications, such as image, sound (LeCun et al., 2015) and natural language processing (Young et al., 2017; Linggard et al., 2012). However, the success…
Highlights Precision medicine will require better data sources of social and behavioural data. Most structured social and behavioural data fields from EHR data are inadequate. NLP of unstructured EHR text could yield a chronological timeline of rich data. Social and…
Abstract Objectives: As electronic mental health records become more widely available, several approaches have been suggested to automatically extract information from free‐text narrative aiming to support epidemiological research and clinical decision‐making. In this paper, we explore extraction of explicit mentions…
