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Deep learning-assistance significantly increases the detection sensitivity of neurosurgery residents for intracranial aneurysms in subarachnoid hemorrhage.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Dec 13, 2024
OBJECTIVE: The purpose of this study was to evaluate the effectiveness of a deep learning model (DLM) in improving the sensitivity of neurosurgery residents to detect intracranial aneurysms on CT angiography (CTA) in patients with aneurysmal subarach...
Exploratory study of extracellular matrix biomarkers for non-invasive liver fibrosis staging: A machine learning approach with XGBoost and explainable AI.
Clinical biochemistry
Dec 13, 2024
BACKGROUND: Novel circulating markers for the non-invasive staging of chronic liver disease (CLD) are in high demand. Although underutilized, extracellular matrix (ECM) components offer significant diagnostic potential. This study evaluates ECM-relat...
A web-based tool for cancer risk prediction for middle-aged and elderly adults using machine learning algorithms and self-reported questions.
Annals of epidemiology
Dec 13, 2024
BACKGROUND: From a global perspective, China is one of the countries with higher incidence and mortality rates for cancer.
Mapping Thrombosis Serum Markers by H-NMR Allied with Machine Learning Tools.
Molecules (Basel, Switzerland)
Dec 13, 2024
Machine learning and artificial intelligence tools were used to investigate the discriminatory potential of blood serum metabolites for thromboembolism and antiphospholipid syndrome (APS). H-NMR-based metabonomics data of the serum samples of patient...
Survival After Radical Cystectomy for Bladder Cancer: Development of a Fair Machine Learning Model.
JMIR medical informatics
Dec 13, 2024
BACKGROUND: Prediction models based on machine learning (ML) methods are being increasingly developed and adopted in health care. However, these models may be prone to bias and considered unfair if they demonstrate variable performance in population ...
Longitudinal Model Shifts of Machine Learning-Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals.
Journal of medical Internet research
Dec 13, 2024
BACKGROUND: In recent years, machine learning (ML)-based models have been widely used in clinical domains to predict clinical risk events. However, in production, the performances of such models heavily rely on changes in the system and data. The dyn...
Real-World and Clinical Trial Validation of a Deep Learning Radiomic Biomarker for PD-(L)1 Immune Checkpoint Inhibitor Response in Advanced Non-Small Cell Lung Cancer.
JCO clinical cancer informatics
Dec 13, 2024
PURPOSE: This study developed and validated a novel deep learning radiomic biomarker to estimate response to immune checkpoint inhibitor (ICI) therapy in advanced non-small cell lung cancer (NSCLC) using real-world data (RWD) and clinical trial data.
A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.
Frontiers in endocrinology
Dec 13, 2024
OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after su...
IL-27 as a novel biomarker for pruritus in nodular prurigo and bullous pemphigoid.
Frontiers in immunology
Dec 13, 2024
INTRODUCTION: Bullous pemphigoid (BP) and prurigo nodularis (PN) are chronic pruritic skin diseases that severely impact patients' quality of life. Despite the widespread attention these two diseases have garnered within the dermatological field, the...
Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction.
Frontiers in immunology
Dec 13, 2024
BACKGROUND: Cancer remains a leading cause of mortality worldwide. A non-invasive screening solution was required for early diagnosis of cancer. Multi-cancer early detection (MCED) tests have been considered to address the challenge by simultaneously...
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