Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Application of Generative Artificial Intelligence in Dyslipidemia Care
3
Zitationen
2
Autoren
2025
Jahr
Abstract
Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable. GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice. Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.422 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.300 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.734 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.519 Zit.