5 Result(s)
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Article
Optimizing risk-based breast cancer screening policies with reinforcement learning
Screening programs must balance the benefit of early detection with the cost of overscreening. Here, we introduce a novel reinforcement learning-based framework for personalized screening, Tempo, and demonstra...
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Article
Open AccessPatient-specific COVID-19 resource utilization prediction using fusion AI model
The strain on healthcare resources brought forth by the recent COVID-19 pandemic has highlighted the need for efficient resource planning and allocation through the prediction of future consumption. Machine le...
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Article
Open AccessFusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Advancements in deep learning techniques carry the potential to make significant contributions to healthcare, particularly in fields that utilize medical imaging for diagnosis, prognosis, and treatment decisio...
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Article
Open AccessAuthor Correction: PENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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Article
Open AccessPENet—a scalable deep-learning model for automated diagnosis of pulmonary embolism using volumetric CT imaging
Pulmonary embolism (PE) is a life-threatening clinical problem and computed tomography pulmonary angiography (CTPA) is the gold standard for diagnosis. Prompt diagnosis and immediate treatment are critical to ...
