Digital Twins for Patient Care via Knowledge Graphs and Closed-Form Continuous-Time Liquid Neural Networks

Digital twin technology has is anticipated to transform healthcare, enabling personalized medicines and support, earlier diagnoses, simulated treatment outcomes, and optimized surgical plans. Digital twins are readily gaining traction in industries like manufacturing, supply chain logistics, and civil infrastructure. Not in patient care, however. The challenge of modeling complex diseases with multimodal patient data and the computational complexities of analyzing it have stifled digital twin adoption in the biomedical vertical. Yet, these major obstacles can potentially be handled by approaching these models in a different way. This paper proposes a novel framework for addressing the barriers to clinical twin modeling created by computational costs and modeling complexities. We propose structuring patient health data as a knowledge graph and using closed-form continuous-time liquid neural networks, for real-time analytics. By synthesizing multimodal patient data and leveraging the flexibility and efficiency of closed form continuous time networks and knowledge graph ontologies, our approach enables real time insights, personalized medicine, early diagnosis and intervention, and optimal surgical planning. This novel approach provides a comprehensive and adaptable view of patient health along with real-time analytics, paving the way for digital twin simulations and other anticipated benefits in healthcare.Comment: 6 page

Psychological distress among primary school teachers: a comparison with clinical and population samples

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Objectives: This analysis explored the level of psychological distress among primary school teachers in the South West of England as compared to clinical and general population samples. Study design: Secondary analysis of data from the Supporting Teachers And childRen in Schools (STARS) trial completed by up to 90 teachers at baseline, 9, 18 and 30 months of follow up. Methods: We used the Everyday Feelings Questionnaire (EFQ) as a measure of psychological distress. Baseline data on teachers were compared with a population sample of professionals and a clinical sample of patients attending a depression clinic. Results: Our teacher cohort experienced higher levels of psychological distress than comparable professionals from the general population, which were sustained over 30 months follow-up. Levels of psychological distress were lower than those found in the clinical sample. Using a cut-point indicative of moderate depression, our data suggest between 19% and 29% of teachers experienced clinically significant distress at each time-point. Conclusions: We detected high and sustained levels of psychological distress among primary school teachers, which suggests an urgent need for intervention. Effective support for teachers’ mental health is particularly important given the potential impact of poor teacher mental health on pupil wellbeing, pupil attainment and teacher-pupil relationships.The STARS trial was funded by the National Institute for Health Research Public Health Research Programme (project number 10/3006/07) and the National Institute for Health Research (NIHR) Collaboration for Leadership in Applied Health Research and Care South West Peninsula

Psychological distress among primary school teachers: a comparison with clinical and population samples

Objectives This analysis explored the level of psychological distress among primary school teachers in the South West of England as compared with clinical and general population samples. Study design Secondary analysis of data from the Supporting Teachers and Children in Schools (STARS) trial completed by up to 90 teachers at baseline, 9, 18 and 30 months of follow-up. Methods We used the Everyday Feelings Questionnaire (EFQ) as a measure of psychological distress. Baseline data on teachers were compared with a population sample of professionals and a clinical sample of patients attending a depression clinic. Results Our teacher cohort experienced higher levels of psychological distress than comparable professionals from the general population, which were sustained over 30 months of follow-up. Levels of psychological distress were lower than those found in the clinical sample. Using a cut-point indicative of moderate depression, our data suggest that between 19% and 29% of teachers experienced clinically significant distress at each time-point. Conclusions We detected high and sustained levels of psychological distress among primary school teachers, which suggests an urgent need for intervention. Effective support for teachers’ mental health is particularly important given the potential impact of poor teacher mental health on pupil well-being, pupil attainment and teacher–pupil relationships