AIMC Journal:
Phlebology

ObjectiveEffective patient communication is critical in acute deep vein thrombosis (DVT) management. This study evaluated and compared the intelligibility and clinical appropriateness of patient-directed explanations for acute DVT generated by vascul...

BackgroundLipedema is a frequently misdiagnosed chronic condition that significantly impacts patients' quality of life. As artificial intelligence (AI)-based large language models (LLMs) become increasingly integrated into healthcare communication, t...

ObjectivesGenerative artificial intelligence (AI) models capable of producing photorealistic medical images are increasingly proposed for patient education, clinical illustration, and trainee instruction. However, their ability to accurately represen...

ObjectivesLipedema is a chronic disorder characterized by pain and disproportionate fat distribution, and its diagnosis is frequently overlooked. The aim of this study was to evaluate and compare the responses generated by contemporary artificial int...

BackgroundThis study aims to systematically evaluate the current landscape of artificial intelligence (AI) and machine learning applications in lymphedema research by employing bibliometric and altmetric analyses. The goal is to identify major trends...

BackgroundThis study aimed to develop multiple machine learning (ML) models to predict DVT stability based on clinical and computed tomography (CT) texture features.MethodsA total of 108 patients diagnosed with DVT by clinical examination and ultraso...