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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Adaptive deep brain stimulation (DBS) provides individualized therapy for people with Parkinson’s disease (PWP) by adjusting the stimulation in real-time using neural signals that reflect their motor state. Current algorithms, however, utilize condensed and…
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Large-scale and detailed analyses of activity in the United States (US) remain limited. In this work, we leveraged the comprehensive wearable, demographic, and survey data from the All of Us Research Program, the largest…
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Unnecessary preoperative testing poses a risk to patient safety, causes surgical delays, and increases healthcare costs. We describe the effects of implementing a fully EHR-integrated closed-loop clinical decision support system (CDSS) for placing automatic…
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Generating realistic synthetic health data (e.g., electronic health records), holds promise for fundamental research, AI model development, and enhancing data privacy safeguards. Generative Adversarial Networks (GANs) have been employed for this purpose, but their…
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Autonomous artificial intelligence (AI) for pediatric diabetic retinal disease (DRD) screening has demonstrated safety, effectiveness, and the potential to enhance health equity and clinician productivity. We examined the cost-effectiveness of an autonomous AI strategy…
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