Latest AI and machine learning research in pediatrics for healthcare professionals.
Neonatal seizures cause significant morbidity and mortality, both acutely and in the long term, contributing to adverse neurodevelopmental outcomes. Traditional EEG seizure detection by human experts is constrained by limited efficiency, scalability, and objectivity, which can lead to delay diagnosis and hinder optimal outcomes. Deep learning methods have shown promise neonatal seizure detection, ...
With dementia diagnoses in the UK projected to exceed one million in 2025, there is an urgent need for scalable and effective care solutions to ease pressure on health and social care systems. Artificial Intelligence (AI)-enabled smart home systems are emerging as promising digital health innovations, offering cognitive support, real-time monitoring, and decision-making assistance. However, concer...
Accurate, affordable tuberculosis (TB) diagnostics that do not require sputum samples are urgently needed for TB control and elimination. Prior serolo...
Medication in hospitalised infants is often prescribed using a ‘one-size-fits-all’ approach due to lack of clinical biomarkers. Caffeine is one of the...
Digital parenting restrictions are widely used to manage adolescent screen use, yet it is unclear how effective these strategies remain as children ag...
Unintended pregnancy remains common in high income countries and has been linked to poorer maternal and neonatal outcomes. Whether pregnancy intention...
Lower respiratory tract infection (LRTI) is a leading cause of morbidity and mortality among children admitted to paediatric intensive care units (PIC...
The 2022 global outbreak of clade IIb mpox represented a turning point in public health’s handling of poxviruses. The primary vaccine available for pr...
The clinical promise of Large Language Models (LLMs) is often unrealized due to pro-hibitive computational costs. These costs create barriers not only...
Electronic health record (EHR) data often missed care outside a given health system, resulting in data discontinuity. We aimed to: (1) quantify miscla...
The concept of fairness has been extensively examined within the domains of Machine Learning and Artificial Intelligence more broadly. It remains, how...
Diagnosis of asthma in primary care is challenged by a multistep pathway with variable adherence leading to significant misdiagnosis, late diagnosis a...
Interpretable scoring system can contribute to bridge the gap between the timeliness and complexity of diagnosing Alzheimer’s disease (AD) and promote...
Medication use during adolescence provides important insight into current health and treatment patterns. However, these data are often difficult to an...
UK ambulance services face record demand, resourcing challenges and rising clinical documentation burden. Ambient voice technology (AVT) coupled with ...
Leg dystonia in cerebral palsy (CP) is debilitating but remains underdiagnosed. Routine clinical evaluation has only 12% accuracy for leg dystonia dia...
Acute appendicitis is a common but diagnostically challenging surgical emergency in children. Existing linear scoring systems lack sufficient accuracy...
Cerebral Palsy (CP), affecting approximately 1 in 500 children due to abnormal brain development, impacts movement control. Early risk assessment via ...
Reducing the global burden of disease is crucial for improving health outcomes worldwide. However, misalignment between health aid and country-level d...
The adoption of artificial intelligence in dermatology promises democratized access to healthcare, but model reliability depends on the quality and co...