Latest AI and machine learning research in ethics for healthcare professionals.
BackgroundHealth care organizations are increasingly required to make strategic decisions about artificial intelligence (AI) systems before their clinical value, operational consequences, governance requirements, and workforce implications are fully known. Clinical AI pilots can reduce this uncertainty only if they generate management-relevant evidence beyond retrospective model performance, inclu...
Despite increasing scale and resolution, many biological measurements remain destructive, revealing only spatial information rather than the dynamics it encodes. By combining flexible representations with mechanistic constraints, physics-informed machine learning offers a promising route to inferring these dynamics from static snapshots. Motivated by subcellular imaging of gene expression, we ask ...
Background: Large language models (LLMs) are increasingly deployed in healthcare, where they may adopt different stakeholder perspectives, yet the eff...
Alternating recurrent events -- event-times of a specific nature that trigger a secondary refractory period -- occur in a wide-range of fields, includ...
Introduction: Generative artificial intelligence (AI) can produce realistic clinical scenarios on demand and deliver immediate, individualized feedbac...
Purpose: To evaluate the feasibility and challenges of heart chamber segmentation from non-contrast CT scans using contrastive unpaired image translat...
Background: Children and young people (CYP) are particularly affected by mental health problems. Mobile apps provide a scalable and accessible approac...
Characterising human brain connectivity remains a major challenge in neuroscience. Multimodal datasets combining diffusion MRI with high-resolution mi...
Physics-Informed Neural Networks (PINNs) solve Partial Differential Equations (PDEs) by embedding physical laws into neural network training. However,...
Pulsatile milk transport through the lactating mammary ductal tree involves complex interactions between pressure gradients, wall compliance, and non-...
Physics-Informed Neural Networks (PINNs) are an attractive tool for partial-observation problems in biology, where the governing dynamics are known bu...
Background: Long-acting pre-exposure prophylaxis (PrEP) expands HIV prevention options for women. However, PrEP impact depends on addressing persisten...
Non-canonical HLA-presented peptides are promising therapeutic targets, but their low abundance makes them difficult to reproducibly identify and quan...
Introduction Obstructive lung diseases (OLDs) are responsible for high rates of illness and death worldwide. Inflammation, chronic airflow limitation,...
Background: Non-communicable diseases (NCDs) represent a critical public health challenge in Kenya, responsible for over 50% of inpatient admissions a...
Cardiac function evaluation necessitates continuous, non-invasive monitoring, a capability limited in MRI. Millimeter-wave (mmWave) radar and its Synt...
Participatory qualitative methods such as Photovoice are increasingly used to link research with social action. Recent advances in artificial intellig...
Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for...
Glioblastoma multiforme (GBM) is characterised by profound genomic heterogeneity and heavy-tailed gene-expression distributions that challenge convent...
Parameter estimation in nonlinear biological dynamical systems is a difficult inverse problem because the governing equations are often stiff or oscil...