Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Artificial Intelligence Algorithms in Biomedical Application
4
Zitationen
1
Autoren
2023
Jahr
Abstract
In recent years, the rapid development of artificial intelligence (AI) has accelerated the development of many social industries. In view of the demand for large data collection and effective medical data processing, AI has undoubtedly become an important part of biomedical research. Medical professionals can accurately diagnose and treat a variety of symptoms in patients with the help of AI algorithms. Modern AI technologies, such as traditional neural networks for structured data and natural language processing for unstructured data, can accurately analyze various medical data. The medical industry uses these AI learning techniques for disease diagnosis, drug discovery, and medical image analysis. Against this backdrop, this paper focuses on the application of AI algorithms in biomedicine and examined cases from biomedical research in addition to the introduction of machine learning, deep learning, and transformer models. Last but not least, we briefly introduce the progress of AI in biomedicine and the difficulties it will encounter.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.231 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.084 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.444 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 · 5.423 Zit.