+ HEALTH Background Discharge letters are essential for continuity of care, yet patients often misunderstand their con…± HEALTH Hematoxylin and Eosin (H&E) glass slide preparation is fundamental to histopathology. Pathologists' expertise…+ CLIMATE Traditional soil heavy metal risk assessments suffer from fragmented indices and poor logical integration. Co…± HEALTH Background Neonatal pneumothorax can progress rapidly, yet detection on supine chest radiographs remains chal…+ HEALTH T cell exhaustion has widespread implications for the progression and treatment of chronic diseases including…+ HEALTH Background Standard pulmonary arterial hypertension (PAH) risk models may not fully apply to PAH associated w…+ HEALTH Objectives To map and synthesize the scientific evidence regarding the use of Augmented Reality (AR) and Mixe…± HEALTH Objective To examine whether the outputs of machine learning algorithms designed to predict risk of cardiovas…
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Health · Diagnostics & Imaging

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Beyond bias: using AI to reduce diagnostic noise and manage novelty in clinical reasoning

Objectives This study examines AI's capacity to mitigate noise-related diagnostic errors, evaluates its impact on accuracy, and explores the interplay between AI-driven efficiency and human clinical reasoning, particularly in rare or complex cases. Background: Diagnostic errors in clinical reasoning are significantly influenced by noise - random unwanted variability in expert judgments - distinct from cognitive biases. Despite debiasing efforts, noise persists, contributing to adverse events. Artificial intellig…

Diagnosis · Health

Beyond bias: using AI to reduce diagnostic noise and manage novelty in clinical reasoning
AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases
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AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases

Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosis and the high cost of current screening tools. Artificial intelligence (AI) and multimodal retinal imaging offer a non-invasive and viable approach for early risk stratification and longitudinal monitoring. This review highlights how changes in the retinal vasculature and nerve layers are markers of underlying pathophysiologies related to cardiovascular, metabolic…

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