OBJECTIVE: To construct a non-invasive pre-hospital screening model and early based on artificial intelligence algorithms to provide the severity of stroke in patients, provide screening, guidance and early warning for stroke patients and their famil...
OBJECTIVES: Urinary stones composed of uric acid can be treated with medicine. Computed tomography (CT) can diagnose urinary stone disease, but it is difficult to predict the type of uric stones. This study aims to develop a method to distinguish pur...
European review for medical and pharmacological sciences
Nov 1, 2024
OBJECTIVE: End-stage renal disease (ESRD) commonly manifests with disrupted calcium balance, leading to renal osteodystrophy. We posited that variations in the genetic makeup of vitamin D and calcium-sensing receptors, specifically single nucleotide ...
() is a widely disseminated betaherpesvirus that typically induces latant infections. In immunocompromised populations, especially transplant and HIV-infected patients, infection increases in-hospital mortality. Although machine learning models ha...
Journal of cellular and molecular medicine
Nov 1, 2024
Programmed cell death (PCD) pathways hold significant influence in the etiology and progression of a variety of cancer forms, particularly offering promising prognostic markers and clues to drug sensitivity for lung adenocarcinoma (LUAD) patients. We...
Journal of cellular and molecular medicine
Nov 1, 2024
Rupture of advanced carotid atherosclerotic plaques increases the risk of ischaemic stroke, which has significant global morbidity and mortality rates. However, the specific characteristics of immune cells with dysregulated function and proven biomar...
BACKGROUND: The demand for fresh strategies to analyze intricate multidimensional data in neuroscience is increasingly evident. One of the most complex events during our neurodevelopment is adolescence, where our nervous system suffers constant chang...
Background It is unclear whether artificial intelligence (AI) explanations help or hurt radiologists and other physicians in AI-assisted radiologic diagnostic decision-making. Purpose To test whether the type of AI explanation and the correctness and...
Background Deep learning (DL) algorithms have shown promising results in mammographic screening either compared to a single reader or, when deployed in conjunction with a human reader, compared with double reading. Purpose To externally validate the ...
BACKGROUND: Detection of cancer at the early stage currently offers the only viable strategy for reducing disease-related morbidity and mortality. Various approaches for multi-cancer early detection are being explored, which largely rely on capturing...
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