Predicting Severity in Hypertriglyceridemia-Induced Acute Pancreatitis: The Role of Neutrophils, Calcium, and Apolipoproteins.

BACKGROUND Hypertriglyceridemia-induced acute pancreatitis (HTG-AP), representing 10% of all acute pancreatitis cases, is characterized by younger onset age and more severe progression, often leading to higher ICU admission rates. This condition poses a significant challenge due to its rapid progression and the potential for severe complications, including multiple organ failure. HTG-AP is distinct from other forms of pancreatitis, such as those caused by cholelithiasis or alcohol, in terms of clinical presentation and outcomes.

The Application of Artificial Intelligence in Thyroid Nodules: A Systematic Review Based on Bibliometric Analysis.

Background: Thyroid nodules are common lesions in benign and malignant thyroid diseases. More and more studies have been conducted on the feasibility of artificial intelligence (AI) in the detection, diagnosis, and evaluation of thyroid nodules. The aim of this study was to use bibliometric methods to analyze and predict the hot spots and frontiers of AI in thyroid nodules.

Integrating fractional amplitude of low-frequency fluctuation and functional connectivity to investigate the mechanism and prognosis of severe traumatic brain injury.

Objective: Functional magnetic resonance imaging (fMRI) has been used for evaluating residual brain function and predicting the prognosis of patients with severe traumatic brain injury (sTBI). This study aimed to integrate the fractional amplitude of low-frequency fluctuation (fALFF) and functional connectivity (FC) to investigate the mechanism and prognosis of patients with sTBI.

Methods: Sixty-five patients with sTBI were included and underwent fMRI scanning within 14 days after brain injury.

The value of radiomics-based CT combined with machine learning in the diagnosis of occult vertebral fractures.

Purpose: To develop and evaluate the performance of radiomics-based computed tomography (CT) combined with machine learning algorithms in detecting occult vertebral fractures (OVFs).

Materials And Methods: 128 vertebrae including 64 with OVF confirmed by magnetic resonance imaging and 64 corresponding control vertebrae from 57 patients who underwent chest/abdominal CT scans, were included. The CT radiomics features on mid-axial and mid-sagittal plane of each vertebra were extracted.