STUDY OBJECTIVE: Sensitivity for stroke detection in emergency medical communication centers (EMCCs) varies widely. Few studies offer detailed insights into the out-of-hospital pathways of patients with stroke. This study explored the ability of EMCC...
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for depression in patients with major depressive disorder (MDD) and bipolar disorder (BD), but accurate prediction of treatment response remains a challenge. Th...
BACKGROUND & AIMS: Addressing many clinical questions, such as estimating survival differences between living donor (LDLT) and deceased donor liver transplantation (DDLT), relies on observational studies, as randomized-controlled trials (RCTs) are of...
Journal of the Academy of Nutrition and Dietetics
Nov 1, 2025
BACKGROUND: Methods for modeling the relationship between self-reported 24-hour dietary recalls and health outcomes are traditionally based on nutrients and/or dietary patterns. Machine learning (ML), combined with hierarchical representations of die...
BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a promising treatment for major depression disorder (MDD), particularly for treatment-resistant cases. However, identifying translatable biomarkers predictive of treatment outcomes re...
OBJECTIVES: This work aimed to develop an automated method for quantifying the distribution and severity of perfusion changes on CT pulmonary angiography (CTPA) in patients with chronic thromboembolic pulmonary hypertension (CTEPH) and to assess thei...
PURPOSE: To investigate whether the deep learning reconstruction (DLR) combined with contrast-enhancement-boost (CE-boost) technique can improve the diagnostic quality of CT pulmonary angiography (CTPA) at low radiation and contrast doses, compared w...
OBJECTIVES: To evaluate the variability of fully automated airway quantitative CT (QCT) measures caused by different kernels and the effect of kernel conversion.
OBJECTIVES: To investigate whether a content-based image retrieval (CBIR) of similar chest CT images can help usual interstitial pneumonia (UIP) CT pattern classifications among readers with varying levels of experience.
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