The spine journal : official journal of the North American Spine Society
Jul 20, 2024
BACKGROUND CONTEXT: The influence of SDOH on spine surgery is poorly understood. Historically, researchers commonly focused on the isolated influences of race, insurance status, or income on healthcare outcomes. However, analysis of SDOH is becoming ...
We developed an interpretable machine learning algorithm that prospectively predicts the risk of thrombocytopenia in older critically ill patients during their stay in the intensive care unit (ICU), ultimately aiding clinical decision-making and impr...
INTRODUCTION: Radiology plays an integral role in fracture detection in the emergency department (ED). After hours, when there are fewer reporting radiologists, most radiographs are interpreted by ED physicians. A minority of these interpretations ma...
OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine lea...
American journal of obstetrics and gynecology
Jul 19, 2024
BACKGROUND: No universally recognized transperineal ultrasound parameters are available for evaluating stress urinary incontinence. The information captured by commonly used perineal ultrasound parameters is limited and insufficient for a comprehensi...
OBJECTIVES: This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC).
Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an inte...
OBJECTIVE: To establish a machine learning model based on radiomics and clinical features derived from non-contrast CT to predict futile recanalization (FR) in patients with anterior circulation acute ischemic stroke (AIS) undergoing endovascular tre...
OBJECTIVE: To develop a machine learning diagnostic model based on MMP7 and other serological testing indicators for early and efficient diagnosis of biliary atresia (BA).
OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal bone computed tomography (CT) images from ultrashort echo-time magnetic resonance imaging (MRI) scans, thereby addressing the intrinsic limitations of ...
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