Using administrative claims and electronic health records for observational studies is common but challenging due to data limitations. Researchers rely on phenotype algorithms, requiring labor-intensive chart reviews for validation. This study investigates whether case…
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Neonatal seizures require urgent treatment, but often go undetected without expert EEG monitoring. We have developed and validated a seizure detection model using retrospective EEG data from 332 neonates. A convolutional neural network was…
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This systematic review examines four themes of device-based remote monitoring (DRM): technology, patient monitoring and support, integration of DRM into clinical care, and patient engagement, and their impact on hospital service use. We included…
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Accurate prognostication guides optimal clinical management in skin cancer. Merkel cell carcinoma (MCC) is the most aggressive form of skin cancer that often presents in advanced stages and is associated with poor survival rates….
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This article critiques the shift towards personalized AI in healthcare and other high-stakes domains, cautioning that without careful deliberation, customized AI systems can compromise the diversity and reach of human knowledge by restricting exposure…
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Dysphagia, a swallowing disorder, requires continuous monitoring of throat-related events to obtain comprehensive insights into the patient’s pharyngeal and laryngeal functions. However, conventional assessments were performed by medical professionals in clinical settings, limiting persistent…
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Fatigue is prevalent in immune-mediated inflammatory and neurodegenerative diseases, yet its assessment relies largely on patient-reported outcomes, which capture perception but not fluctuations over time. Wearable sensors, like inertial measurement units (IMUs), offer a…
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Digital interventions are increasingly utilized as a lever to promote population health, yet not everyone may equally benefit from them. This umbrella review pooled the insights from available systematic and scoping reviews regarding potential…
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Laparoscopic exploration (LE) is crucial for diagnosing intra-abdominal metastasis (IAM) in advanced gastric cancer (GC). However, overlooking single, tiny, and occult IAM lesions during LE can severely affect the treatment and prognosis due to…
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Label noise is a common and important issue that would affect the model’s performance in artificial intelligence. This study assessed the effectiveness and potential risks of automated label cleaning using an open-source framework, Cleanlab,…
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