Studies in health technology and informatics
May 15, 2025
Pancreatic cancer is a devasting disease which is an increasing cause of cancer mortality. The aim of this study was to characterise, using descriptive statistics, the sociodemographic, risk and clinical characteristics of who develops pancreatic can...
Studies in health technology and informatics
May 15, 2025
This study explores how the integration of predictive models with machine learning and natural language processing can optimise community-based service operations, using Timebanking UK as a case study. The research evaluated these models in terms of ...
Studies in health technology and informatics
May 15, 2025
INTRODUCTION: Acute myocardial infarction (AMI) is highly prevalent (3.8% in developed countries), affecting heterogenous populations, and can be influenced by varied factors, including demographics, clinical risk factors, and comorbidities. Identify...
Studies in health technology and informatics
May 15, 2025
Digital Pathology has provided a platform to use Artificial Intelligence (AI) to assist pathologists with diagnosis and reporting. An AI tool is being developed that analyzes digital Hematoxylin and Eosin (stained tissue) images associated with a ski...
BACKGROUND: Early identification of children at risk of sepsis in emergency departments (EDs) is crucial for timely treatment and improved outcomes. Existing risk scores and criteria for paediatric sepsis are not well-suited for early diagnosis in ED...
OBJECTIVES: Evaluate an Artificial Intelligence (AI) system in breast screening through stratified results across age, breast density, ethnicity and screening centres, from different UK regions.
BACKGROUND: Escalating mental health demand exceeds existing clinical capacity, necessitating scalable digital solutions. However, engagement remains challenging. Conversational agents can enhance engagement by making digital programs more interactiv...
BACKGROUND: Converging evidence indicates an adolescent mental health crisis in Western societies that has developed and exacerbated over the past decade. The proposed driving factors of this trend include more screen time, physical inactivity, and s...
Early identification of patients who require onward referral to social care can prevent delays to discharge from hospital. We introduce an explainable machine learning (ML) model to identify potential social care needs at the first point of admission...
The Journal of antimicrobial chemotherapy
May 2, 2025
INTRODUCTION: Large language models (LLMs) are becoming ubiquitous and widely implemented. LLMs could also be used for diagnosis and treatment. National antibiotic prescribing guidelines are customized and informed by local laboratory data on antimic...
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