BACKGROUND: Accurate prediction of pathological complete response (pCR) and disease-free survival (DFS) in locally advanced rectal cancer (LARC) patients undergoing neoadjuvant chemoradiotherapy (NCRT) is essential for formulating effective treatment...
PURPOSE: This study aimed to identify novel biomarkers for preeclampsia (PE) diagnosis by integrating Weighted Gene Co-expression Network Analysis (WGCNA) with machine learning techniques.
OBJECTIVE: This study aims to establish a new prognostic index using machine learning models to predict the clinical outcomes of triple-negative breast cancer (TNBC) patients receiving neoadjuvant therapy.
BACKGROUND: Inflammation-related biomarkers, such as systemic inflammation score (SIS) and neutrophil-lymphocyte ratio (NLR), are associated with colorectal cancer prognosis. However, the combined role of SIS, NLR, and clinicopathological factors in ...
BACKGROUND: Sepsis is a life-threatening organ dysfunction condition produced by dysregulation of the host response to infection. It is now characterized by a high clinical morbidity and mortality rate, endangering patients' lives and health. The pur...
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS).
BACKGROUND: Diabetic retinopathy (DR) is a major complication of diabetes, leading to severe vision impairment. Understanding the molecular mechanisms, particularly PANoptosis, underlying DR is crucial for identifying potential biomarkers and therape...
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...
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