Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence in Cardiac Healthcare: Advancements in Managing Coronary Artery Disease and Acute Coronary Syndrome
0
Zitationen
5
Autoren
2024
Jahr
Abstract
Artificial Intelligence (AI) is transforming cardiac healthcare. It has evolved newer ways of diagnosing and managing coronary artery disease (CAD) and acute coronary syndrome (ACS), which are leading causes of mortality and morbidity worldwide. AI in healthcare encompasses critical technologies such as machine learning (ML), deep learning (DL), and natural language processing (NLP), which improve diagnostic accuracy and optimize patient management. ML algorithms improve predictive analytics and clinical decision support, while DL, particularly through convolutional neural networks, excels in medical imaging tasks. NLP facilitates the extraction of valuable insights from unstructured clinical data, enhancing patient care. AI-driven tools enhance diagnostic accuracy surpassing traditional methods. Furthermore, AI supports treatment optimization by predicting outcomes based on a multitude of clinical variables, particularly in complex cases with multiple comorbidities. A real-world application of AI in cardiac healthcare is wearable smart devices such as smartwatches, rings, belts, shoes, etc. with real-time remote monitoring capabilities that allow for timely interventions and hence can prevent acute episodes or hospitalizations. Despite the promising advancements, challenges such as ethical implications and concerns about data privacy persist. The application of AI in the healthcare system demands strong regulatory frameworks to ensure patient safety while maximizing the benefits of these technologies. In conclusion, AI integration into cardiac health management represents a significant shift toward more precise and efficient care for patients with CAD and ACS. By leveraging advanced algorithms to analyze complex datasets, healthcare providers can enhance diagnostic accuracy and optimize treatment plans, ultimately improving patient outcomes. The future of cardiology will likely involve a synergistic relationship between AI technologies and human expertise, heralding a new era in cardiovascular medicine.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.292 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.143 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.539 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.452 Zit.