OBJECTIVES: In this study, we propose an interpretable deep learning radiomics (IDLR) model based on [F]FDG PET images to diagnose the clinical spectrum of Alzheimer's disease (AD) and predict the progression from mild cognitive impairment (MCI) to A...
BACKGROUND: Significant variability in outcomes after left ventricular assist device (LVAD) implantation emphasize the importance of accurately assessing patients' risk before surgery. This study assesses the Machine Learning Assessment of Risk and E...
PURPOSE: External physiological monitoring is the primary approach to measure and remove effects of low-frequency respiratory variation from BOLD-fMRI signals. However, the acquisition of clean external respiratory data during fMRI is not always poss...
Applied psychology. Health and well-being
Oct 31, 2024
The promotion of health and provision of care services for new recruits are issues of constant concern for military leaders and healthcare providers, as they are crucial to maintaining and operating military forces. The enhancement of military person...
Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
Oct 31, 2024
BACKGROUND: Contrast-enhanced ultrasound (CEUS) is frequently used to distinguish benign parotid tumors (BPTs) from malignant parotid tumors (MPTs). Introducing machine learning may enable clinicians to preoperatively diagnose parotid tumors precisel...
AIMS: To test the efficacy of artificial intelligence (AI)-assisted Ki-67 digital image analysis in invasive breast carcinoma (IBC) with quantitative assessment of AI model performance.
Computer methods and programs in biomedicine
Oct 31, 2024
BACKGROUND AND OBJECTIVE: Binge eating disorder (BED) is the most frequent eating disorder, often confused with obesity, with which it shares several characteristics. Early identification could enable targeted therapeutic interventions. In this study...
Most patients with non-small cell lung cancer (NSCLC) are diagnosed at an advanced stage of the disease, which complicates treatment due to a heightened risk of metastasis. Consequently, the timely identification of biomarkers associated with lymph n...
PURPOSE: Missed fractures are the most common radiologic error in clinical practice, and erroneous classification could lead to inappropriate treatment and unfavorable prognosis. Here, we developed a fully automated deep learning model to detect and ...
Immunoglobulin light chain (AL) amyloidosis is a severe disorder caused by the accumulation of amyloid fibrils, leading to organ failure. Early diagnosis is crucial to prevent irreversible damage, yet it remains a challenge due to nonspecific symptom...
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