Diagnosing language disorders associated with autism is a complex challenge, often hampered by the subjective nature and variability of traditional assessment methods. In this study, we explored large language models (LLMs) to overcome the…
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What You Should Know:
– Ceribell, Inc. has secured FDA 510(k) clearance for the world’s first continuous, AI-powered delirium monitoring solution, expanding its existing EEG platform beyond seizure detection.
– The technology addresses a massive gap…
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Background: Sleep is essential for overall health and plays a critical role in the diagnosis of psychiatric disorders. Although polysomnography remains the gold standard for measuring sleep, its reliance on laboratory settings limits its…
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Professor Hatim Abdulhussein, chief executive at Health Innovation Kent Surrey Sussex
An initiative called TrustX has been launched to help verify, deploy, and test agentic AI for use across the NHS and social care.
It…
Sensory Health is the initial focus of DigitalHealth.London Healthcare Challenges, a new programme delivered by DigitalHealth.London and the Health Innovation Network South London that brings together clinicians, other health system stakeholders, innovators and people…
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Sjögren’s disease (SjD) is a common systemic autoimmune disease that remains difficult to diagnose early due to non-specific symptoms and lack of definitive biomarkers. This multicentre retrospective cohort study analysed data from 34,958 patients…
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Accurate detection of lung cancer from Computed Tomography (CT) scans is vital for improving patient survival but remains challenging for deep learning models, which struggle with scale variations of pulmonary nodules and the complex…
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Lung cancer remains the top cause of cancer death, demanding consistent decisions. This clinically oriented review synthesizes computer-aided diagnosis across classical imaging, machine learning, and deep learning, emphasizing bedside-proven advances: multimodal CT/PET–clinical fusion; small-data…
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Atrial fibrillation (AF) is the most common arrhythmia worldwide and is associated with significant morbidity and mortality. FibriCheck is a medical analysis platform that uses an end-to-end algorithm to detect AF based on photoplethysmography…
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Current AI approaches for cardiac diagnosis require condition-specific supervised learning with extensive labeled datasets, leading to fundamental scalability barriers. We developed an ECG-CLIP model, applying contrastive multimodal learning to enable zero-shot cardiac diagnosis from…
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