AIMC Journal:
Thoracic research and practice
Showing 1 to 8 of 8 articles
Reply: Artificial Intelligence in Respiratory Medicine: Epistemic Authority, Trust and Responsibility in Practice and in Training.
Thoracic research and practice
Sep 4, 2026
Letter to the Editor: Artificial Intelligence in Respiratory Medicine: Epistemic Authority, Trust and Responsibility in Practice and in Training.
Thoracic research and practice
Aug 31, 2026
Letter to the Editor: Free Large Language Model-based Chatbots Can Help to Align Statistical Tests with the Study Design and Avoid Pseudo-replication.
Thoracic research and practice
Jul 24, 2026
Artificial Intelligence and Accountability in Scientific Writing: The Author's Responsibility.
Thoracic research and practice
Jul 24, 2026
Comparison of AI-based Chatbot Performance in Analyzing Clinical Scenarios versus Medical Residents: A Novel Approach in Chest Diseases Education.
Thoracic research and practice
Apr 14, 2026
OBJECTIVE: Rapid advancements in artificial intelligence (AI) technologies offer new opportunities in medical education. The aim of this study is to compare the performance of large language models, specifically ChatGPT-4 and Gemini, in analyzing cli...
AI in Patient Care: Evaluating Large Language Model Performance Against Evidence-Based Guidelines for Pulmonary Embolism.
Thoracic research and practice
Jan 20, 2026
OBJECTIVE: Artificial intelligence (AI)-driven large language models (LLMs) are increasingly used in patient education; however, their ability to interpret and apply clinical guidelines within real-world physician workflows remains uncertain. Pulmona...
Artificial Intelligence in Pleural Diseases: Current Applications and Next Steps.
Thoracic research and practice
Jan 15, 2026
Pleural diseases pose a significant burden on healthcare systems due to diagnostic challenges and high costs. Artificial intelligence (AI) has the potential to provide faster, more accurate, and more reliable results in the diagnosis of these disease...
Prognostic Significance of Computed Tomography Severity Score for Machine Learning Prediction of Intensive Care Unit Admission in COVID-19 Patients.
Thoracic research and practice
Jan 15, 2026
OBJECTIVE: The computed tomography-severity score (CT-SS) quantifies the severity of pulmonary involvement and is significantly associated with disease severity, intensive care unit (ICU) admissions, and mortality in coronavirus disease-2019 (COVID-1...
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