AIMC Topic: Peripheral Arterial Disease

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Vascular Aging Detected by Peripheral Endothelial Dysfunction Is Associated With ECG-Derived Physiological Aging.

Journal of the American Heart Association
Background An artificial intelligence algorithm that detects age using the 12-lead ECG has been suggested to signal "physiologic age." This study aimed to investigate the association of peripheral microvascular endothelial function (PMEF) as an index...

Use of Natural Language Processing to Improve Identification of Patients With Peripheral Artery Disease.

Circulation. Cardiovascular interventions
BACKGROUND: Peripheral artery disease (PAD) is underrecognized, undertreated, and understudied: each of these endeavors requires efficient and accurate identification of patients with PAD. Currently, PAD patient identification relies on diagnosis/pro...

PredyCLU: A prediction system for chronic leg ulcers based on fuzzy logic; part II-Exploring the arterial side.

International wound journal
Peripheral arterial disease (PAD) and its most severe form, critical limb ischaemia (CLI), are very common clinical conditions related to atherosclerosis and represent the major causes of morbidity, mortality, disability, and reduced quality of life ...

Natural language processing of clinical notes for identification of critical limb ischemia.

International journal of medical informatics
BACKGROUND: Critical limb ischemia (CLI) is a complication of advanced peripheral artery disease (PAD) with diagnosis based on the presence of clinical signs and symptoms. However, automated identification of cases from electronic health records (EHR...

Mining peripheral arterial disease cases from narrative clinical notes using natural language processing.

Journal of vascular surgery
OBJECTIVE: Lower extremity peripheral arterial disease (PAD) is highly prevalent and affects millions of individuals worldwide. We developed a natural language processing (NLP) system for automated ascertainment of PAD cases from clinical narrative n...

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

Journal of vascular surgery
OBJECTIVE: A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aim...

ML-ROM wall shear stress prediction in patient-specific vascular pathologies under a limited clinical training data regime.

PloS one
High-fidelity numerical simulations such as Computational Fluid Dynamics (CFD) have been proven effective in analysing haemodynamics, offering insight into many vascular conditions. However, these methods often face challenges of high computational c...

Predicting Future Cardiovascular Events in Patients With Peripheral Artery Disease Using Electronic Health Record Data.

Circulation. Cardiovascular quality and outcomes
BACKGROUND: Patients with peripheral artery disease (PAD) are at risk of major adverse cardiac and cerebrovascular events. There are no readily available risk scores that can accurately identify which patients are most likely to sustain an event, mak...