Journal of Clinical Medicine, Volume 14, Issue 23
2025 December-1 - 354 articles
Cover Story: Pulmonary arterial hypertension (PAH) is a life-threatening cardiovascular disease with a significant burden of morbidity and mortality. While existing clinical risk assessment tools provide valuable guidance, the precise role of individual clinical parameters in predicting survival remains unclear. This study aims to enhance our understanding of these parameters by leveraging machine learning techniques to identify and rank their importance in predicting mortality among PAH patients. Using the Database of Pulmonary Hypertension in the Polish Population registry dataset and explainable AI methods, this research highlights the potential of artificial intelligence to complement traditional risk assessment approaches, offering clinicians a personalized tool for improved decision-making and patient management. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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