Association between lipid accumulation product and chronic obstructive pulmonary disease: a cross-sectional analysis.

Background: Research indicates that obesity can worsen the clinical manifestations of chronic obstructive pulmonary disease (COPD). Timely detection of COPD has the potential to enhance treatment results. This study seeks to investigate the association between a new metabolic indicator, the lipid accumulation product (LAP), and the risk of developing COPD.

Development of nomograms to predict outcomes for large hepatocellular carcinoma after liver resection.

Background: Large hepatocellular carcinoma (HCC) is difficult to resect and accompanied by poor outcome. The aim was to evaluate the short-term and long-term outcomes of patients who underwent liver resection for large HCC, eventually drawing prediction models for short-term and long-term outcomes.

Methods: 1710 large HCC patients were recruited and randomly divided into the training (n = 1140) and validation (n = 570) cohorts in a 2:1 ratio.

Evaluation of the ability of large language models to self-diagnose oral diseases.

Large language models (LLMs) offer potential in primary dental care. We conducted an evaluation of LLMs' diagnostic capabilities across various oral diseases and contexts. All LLMs showed diagnostic capabilities for temporomandibular joint disorders, periodontal disease, dental caries, and malocclusion.

Tumor burden with AFP improves survival prediction for TACE-treated patients with HCC: An international observational study.

Background & Aims: Current prognostic models for patients with hepatocellular carcinoma (HCC) undergoing transarterial chemoembolization (TACE) are not extensively validated and widely accepted. We aimed to develop and validate a continuous model incorporating tumor burden and biology for individual survival prediction and risk stratification.

Methods: Overall, 4,377 treatment-naive candidates for whom TACE was recommended, from 39 centers in five countries, were enrolled and divided into training, internal validation, and two external validation datasets.

Enhancing smart healthcare networks: Integrating attribute-based encryption for optimization and anti-corruption mechanisms.

This study investigates the feasibility and effectiveness of integrating Attribute-Based Encryption (ABE) into smart healthcare networks, with a particular focus on its role in enhancing anti-corruption mechanisms. The study provides a comprehensive analysis of current vulnerabilities in these networks, identifying potential data security risks. An anti-corruption mechanism is designed to ensure data integrity and reliability.