OBJECTIVE: Acute respiratory distress syndrome (ARDS) is estimated to be prevalent in 10% of ICU patients and results in high mortality rates of up to 45%. The recognition of ARDS can be complex and is often delayed or missed entirely. Recognition of...
Dementia is among the most distressing and burdensome health challenges in aging populations. Treatment efficacy is limited; however, early diagnosis can delay or prevent disease progression. Previous machine learning-based prediction models have lim...
Acute kidney injury is a common and critical complication in patients with community-acquired pneumonia who are admitted to intensive care units, substantially increasing their risk of short-term mortality. To enhance early clinical decision-making, ...
BACKGROUND: Renal cell carcinoma (RCC), which accounts for 70-90% of kidney malignancies, remains difficult to diagnose early due to its asymptomatic onset and the lack of reliable biomarkers. This study aimed to develop a robust diagnostic model by ...
Gastric cancer (GC) is a leading cause of cancer-related mortality globally. Histone lactylation, an emerging post-translational modification, holds promise as a therapeutic target and prognostic biomarker, though its expression patterns and clinical...
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a growing global health challenge. Conventional diagnostic tools have limited sensitivity and specificity for early-stage disease. In this context, long non-coding RNAs (lncRNAs) have emerged as promisin...
BACKGROUND: Low back pain imposes a substantial burden on global healthcare systems. Kinesiophobia is highly prevalent among older adults with chronic low back pain, severely hindering effective intervention and treatment. However, current assessment...
Early detection of lung cancer is crucial for improving patient outcomes. However, accurately diagnosing invasive pulmonary nodules and predicting tumor invasiveness remain major clinical challenges. Given the established role of immune dysfunction i...
The main objective of osteoporosis management is to prevent osteoporotic fractures. Using machine learning methods, new risk variables can be identified to enhance the ability to identify women with osteoporosis who are at an increased risk of bone f...
The COVID-19 pandemic has placed immense pressure on global healthcare systems, underscoring the urgent need for early and accurate prediction of disease severity to improve patient care and optimize resource allocation. Failure in ward allocation ca...
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