Publications by authors named "Elodie Labrecque Langlais"
Background: Early recognition of volume overload is essential for heart failure patients. Volume overload can often be easily treated if caught early but causes significant morbidity if unrecognized and allowed to progress. Intravascular volume status can be assessed by ultrasound-based estimation of right atrial pressure (RAP), but the availability of this diagnostic modality is limited by the need for experienced physicians to accurately interpret these scans.
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- - The article examines how artificial intelligence (AI) can enhance patient outcomes in acute cardiac care by quickly analyzing data for predicting and diagnosing heart conditions.
- - It discusses AI's role in various diagnostic tools like echocardiography and ECGs, while also addressing regulatory issues and categorizing AI algorithms based on their risk levels.
- - The review highlights challenges such as data quality and bias, stressing the importance of thorough validation and inclusive data, and emphasizes the need for continued research and regulation to effectively integrate AI into healthcare.
The potential of artificial intelligence (AI) in medicine lies in its ability to enhance clinicians' capacity to analyse medical images, thereby improving diagnostic precision and accuracy and thus enhancing current tests. However, the integration of AI within health care is fraught with difficulties. Heterogeneity among health care system applications, reliance on proprietary closed-source software, and rising cybersecurity threats pose significant challenges.
View Article and Find Full Text PDFThe coronary angiogram is the gold standard for evaluating the severity of coronary artery disease stenoses. Presently, the assessment is conducted visually by cardiologists, a method that lacks standardization. This study introduces DeepCoro, a ground-breaking AI-driven pipeline that integrates advanced vessel tracking and a video-based Swin3D model that was trained and validated on a dataset comprised of 182,418 coronary angiography videos spanning 5 years.
View Article and Find Full Text PDFCardiovascular diseases are the leading cause of death globally and contribute significantly to the cost of healthcare. Artificial intelligence (AI) is poised to reshape cardiology. Using supervised and unsupervised learning, the two main branches of AI, several applications have been developed in recent years to improve risk prediction, allow large-scale analysis of medical data, and phenotype patients for personalized medicine.
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