Effective hemodynamic management in the intensive care unit requires individualized targets that adapt to dynamic clinical conditions. We developed Dynamic Cohort Ensemble Learning (DynaCEL), a real-time framework that recommends personalized heart rate and systolic…
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Intraoperative frozen section diagnosis provides essential, real-time histological insights to guide surgical decisions. However, the quality of these time-sensitive sections is often suboptimal, posing significant diagnostic challenges for pathologists. To address these limitations, we…
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Long COVID poses a significant disease burden globally, but its heterogeneous presentation and unreliable coding practices render it difficult to study. Developing efficient phenotyping algorithms is crucial to enabling risk prediction and effective management…
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Thalassemia is an inherited blood disorder. Current diagnostic methods mainly rely on sophisticated equipment and specifically trained technicians. This study aims to identify and genotype thalassemia by applying machine learning (ML) algorithms to routine…
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A computer-aided detection (CAD) system for early esophagus carcinoma identification during endoscopy with narrow-band imaging (NBI) was evaluated in a large-scale, prospective, tandem, randomized controlled trial to assess its effectiveness. The study was registered…
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Endovascular treatment (EVT) for vertebrobasilar artery occlusion (VBAO) with atrial fibrillation presents complex clinical challenges. This comprehensive multicenter study of 525 patients across 15 Chinese provinces investigated nuanced predictors beyond conventional metrics. While 45.1%…
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Differentiating between diabetic nephropathy (DN) and non-diabetic renal disease (NDRD) without a kidney biopsy remains a major challenge, often leading to missed opportunities for targeted treatments that could greatly improve NDRD outcomes. To reform…
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Electronic Health Record (EHR) systems are particularly valuable in pediatrics due to high barriers in clinical studies, but pediatric EHR data often suffer from low content density. Existing EHR code embeddings tailored for the…
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Machine learning and artificial intelligence (AI/ML) models in healthcare may exacerbate health biases. Regulatory oversight is critical in evaluating the safety and effectiveness of AI/ML devices in clinical settings. We conducted a scoping review…
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Although computerized cognitive training (CCT) is an effective digital intervention for cognitive impairment, its dose-response relationship is understudied. This retrospective cohort study explores the association between training dose and cognitive improvement to find the…
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