Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...
ccRCC is an aggressive, heterogeneous tumor with a poor prognosis. Prognostic assessments need multi-modal data. Radiological images have limits, while pathological images offer micro-level details. Integrating these for ccRCC outcome prediction is i...
Advanced cervical cancer (aCC) is associated with a poor prognosis. This study aimed to develop and validate a deep learning-based risk stratification model to predict overall survival in aCC patients using pre-treatment CT images. A total of 396 pat...
Traditional hematoxylin and eosin staining in formalin-fixed paraffin-embedded sections, while essential for diagnostic pathology, is time-consuming, labor intensive, and prone to artifacts that can obscure critical histological details. Label-free u...
OBJECTIVE: To construct and validate a predictive model for the risk of postoperative constipation in middle-aged and elderly patients with lower limb fractures based on machine learning algorithms, so as to provide decision-making support for clinic...
Primary myelofibrosis (PMF) is a heterogeneous bone marrow disorder, and substantial evidence indicates the involvement of inflammatory mediators in its progression. However, a diagnostic model based on inflammation-related genes has not yet been est...
Gastric cancer (GC) remains one of the most prevalent and lethal malignancies worldwide, necessitating the development of efficient, non-invasive methods for early detection. In this study, a serum diagnostic approach based on shell-isolated nanopart...
BACKGROUND: Acute Respiratory Distress Syndrome (ARDS) remains a critical condition associated with high mortality rates, prolonged hospitalization, and reduced quality of life despite advances in critical care. The albumin-corrected anion gap (ACAG)...
Perioperative stroke significantly impacts postoperative outcomes. Current risk stratification methods for perioperative stroke prediction lack accuracy and practicality. We aimed to develop a machine learning (ML) model that improves both accuracy a...
Deep learning tools based on computer vision have emerged as alternative methods for assessing radiographic image patterns. These approaches have been explored for various forensic applications, including sex and age estimation. This study aimed to e...
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