We describe novel computational techniques for constructing induction rules deductive synthesis proofs. Deductive holds out the promise of automated construction correct computer programs from specifications their desired behaviour. Synthesis with iteration or recursion requires inductive proof, but standard appropriate are restricted to recycling recursive structure specifications. What is needed rule that can introduce structures. show a combination rippling and use meta-variables as...

Neurosymbolic artificial intelligence (AI) is an increasingly active area of research that combines symbolic reasoning methods with deep learning to leverage their complementary benefits. As knowledge graphs (KGs) are becoming a popular way represent heterogeneous and multirelational data, for on graph structures have attempted follow this neurosymbolic paradigm. Traditionally, such approaches utilized either rule-based inference or generated representative numerical embeddings from which...

Prediction of survival in patients diagnosed with a brain tumour is challenging because heterogeneous behaviours and treatment response. Advances machine learning have led to the development clinical prognostic models, but due lack model interpretability, integration into practice almost non-existent. In this retrospective study, we compare five classification models varying degrees interpretability for prediction greater than one year following diagnosis.1028 aged ≥16 years diagnosis...

<title>Abstract</title> Background As the prevalence of multimorbidity grows, provision effective healthcare is more challenging. Both and complexity in delivery may be associated with worse outcomes. Methods We studied consecutive, unique emergency non-surgical hospitalisations for patients over 50 years old to three hospitals Scotland, UK between 2016 2024 using linked primary care hospital records define (2 + long-term conditions), timestamped electronic health record (EHR) contacts...

We present a novel formalisation of tensor semantics for linear temporal logic on finite traces (LTLf), with formal proofs correctness carried out in the theorem prover Isabelle/HOL. demonstrate that this can be integrated into neurosymbolic learning process by defining and verifying differentiable loss function LTLf constraints, automatically generating an implementation integrates PyTorch. show that, using loss, learns to satisfy pre-specified logical constraints. Our approach offers fully...

Abstract Studies of how multiple long-term conditions (MLTC) cluster together in individuals vary the populations studied, and whether they age and/or sex stratify, which limits comparison between studies reproducibility. This study uses a large, UK primary-care dataset to examine pairwise strength association 74 varies by both men women aged 30-99 years, explore implications for MLT analyses. Joint prevalence was lowest younger age-groups progressively increased with age, whereas...

As the prevalence of multimorbidity grows, provision effective healthcare is more challenging. Both and complexity in delivery may be associated with worse outcomes. We studied consecutive, unique emergency non-surgical hospitalisations for patients over 50 years old to three hospitals Scotland, UK between 2016 2024 using linked primary care hospital records define (2 + long-term conditions), timestamped electronic health record (EHR) contacts nursing rehabilitation providers describe...

understanding care-home outbreaks of COVID-19 is a key public health priority in the ongoing pandemic to help protect vulnerable residents.to describe all infection Scottish care-homes for older people between 01/03/2020 and 31/03/2020, with follow-up 30/06/2020.National linked data cohort analysis people.data linkage was used identify care-homes. Care-home characteristics associated presence an outbreak were examined using logistic regression. Size modelled negative binomial regression.334...

We give an overview of a rigorous approach to Web Services composition based on theorem proving in the proof assistant HOL Light. In this, we exploit proofs-as-processes paradigm compose multiple specified Classical Linear Logic, while using expressive nature our theorem-proving framework provide systematic and treatment properties such as exceptions. The end result is not only formally verified composition, with associated guarantee correctness, but also 'executable' π-calculus statement...

Abstract Background The impact of the COVID-19 pandemic on long-term care residents remains wide interest, but most analyses focus initial wave infections. Objective To examine change over time in: (i) size, duration, classification and pattern care-home outbreaks associated mortality (ii) characteristics with an outbreak. Design Retrospective observational cohort study using routinely-collected data. Setting All adult care-homes in Scotland (1,092 homes, 41,299 places). Methods Analysis was...

BackgroundRobustly examining associations between long-term conditions may be important in identifying opportunities for intervention multimorbidity but is challenging when evidence limited. We have developed a Bayesian inference framework that robust to sparse data and used it quantify morbidity the oldest old, population with limited available data.MethodsWe conducted retrospective cross-sectional study of representative dataset primary care patients Scotland as March 2007. included 40...

Many hospitalised patients require rehabilitation during recovery from acute illness. We use routine data Electronic Health Records (EHR) to report the quantity and intensity of required achieve hospital discharge, comparing with without COVID-19.

Neurosymbolic AI is an increasingly active area of research that combines symbolic reasoning methods with deep learning to leverage their complementary benefits. As knowledge graphs are becoming a popular way represent heterogeneous and multi-relational data, for on graph structures have attempted follow this neurosymbolic paradigm. Traditionally, such approaches utilized either rule-based inference or generated representative numerical embeddings from which patterns could be extracted....

AbstractWe propose a computer-based framework for the formal verification of collaboration patterns in healthcare teams. In this, are constructed diagrammatically as compositions keystones that viewed abstract processes. The approach provides mechanisms ensuring safety properties enforced and exceptional events handled systematically. Additionally, fully verified, executable model is obtained an end product, enabling simulation its associated scenarios.Keywords:...