The growth of generative AI and easily available Open Access health datasets has transformed researcher productivity, leading to an explosion in publications that has in part been attributed to paper mills (organisations that provide manuscripts for ... read more
PurposeMELD Graph is a state-of-the-art artificial intelligence (AI) model for automated detection of focal cortical dysplasia (FCD), but its performance remains limited, highlighting the need to investigate which aspects of the pipeline affect its a... read more
Brain tumors are among the most lethal cancers with gliomas representing the most morphologically complex type. Precise and time efficient glioma segmentation and classification are essential for accurate diagnosis, treatment planning, and patient mo... read more
BackgroundSystemic infections are a leading cause of hospitalization and death among patients with cirrhosis. Timely and accurate infection identification is essential for both clinical care and the development of predictive models. However, existing... read more
Patellofemoral pain (PFP) is a common running related injury associated with several biomechanical factors such as altered kinematics and kinetics across lower extremity joints. Prior research suggests mechanisms for PFP may differ within those affec... read more
Severe motor impairments such as amyotrophic lateral sclerosis and locked-in syndrome lead to partial or complete loss of speech, severely restricting communication as voluntary motor control deteriorates. In this study, we developed a non-invasive, ... read more
BackgroundArtificial intelligence (AI) scribes have the potential to reduce documentation burden. Previous studies have mostly relied on aggregated, vendor-provided (e.g., Epics Signal) outcome measures, potentially obfuscating the true effect of AI ... read more
Primary ciliary dyskinesia (PCD) belongs to the group of rare genetic disorders that is extremely hard to diagnose and treat. Current diagnostic modalities detect only 70% of cases and are technically demanding. It necessitates novel computational ap... read more
Genomic and protein foundation models (GFMs and PFMs) have demonstrated strong performance in learning the language of DNA and proteins, but their use in large-scale sequence generation is limited by the latency of autoregressive decoding. Because ev... read more
Humans can readily recognize words even when they are misspelled, though with slower responses, demonstrating remarkable robustness in reading. The computational mechanisms underlying this combination of robustness and cost in reading remain unclear.... read more
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