The neonatal period is critical and stressful, particularly in low-resource settings where existing monitoring methods for newborns are sporadic and labor-intensive. There is a pressing need for an affordable, user-friendly device that offers continuous…
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Artificial intelligence (AI) has become a fundamental tool for assisting clinicians in analyzing ophthalmic images, such as optical coherence tomography (OCT). However, developing AI models often requires extensive annotation, and existing models tend to…
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The rapid development of AI solutions reveals opportunities to address the underdiagnosis and poor management of chronic conditions in developing settings. Using the method of simulated patients and experimental designs, we evaluate the quality,…
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We developed a deep residual network (ResNet) framework to classify thyroid cancer differentiation states by integrating multiomic data and interpretability analysis. Our framework incorporated untargeted metabolomic, whole-exome sequencing, and transcriptomic data from 158 thyroid…
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Deep learning has proven to be an excellent tool for interpreting medical images in adults and children. However, it is still underdeveloped for neonates. This study developed NeoCLIP, a novel deep contrastive learning model…
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Hospital readmission is a key quality metric, yet post-discharge interventions often yield variable results. In the first large-scale randomized evaluation of causal machine learning in a health system, we assessed whether a novel model…
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The emergence of portable imaging devices improves medical image acquisition efficiency in resource-limited regions, but a shortage of medical personnel still limits timely diagnosis. We propose Embed-MedSAM, a fully automatic segmentation model with low…
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Overeating contributes to obesity and poses a significant public health threat. The SenseWhy study (2018–2022) monitored 65 individuals with obesity in free-living settings, collecting 2302 meal-level observations (48 per participant), using an activity-oriented wearable…
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FDA Advisory Committee Meeting Overview
The Food and Drug Administration (FDA) is taking a significant step forward in evaluating artificial intelligence applications in healthcare by convening its Digital Health Advisory Committee on November 6, 2024….
This paper aims to build a model that can Segment Anything in 3D medical images, driven by medical terminologies as Text prompts, termed as SAT. Our main contributions are three-fold: (i) We construct the…
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