Artificial Intelligence-Empowered Radiology—Current Status and Critical Review
Jagiellonian University · AGH University of Krakow · +2 more institutions
Abstract
Humanity stands at a pivotal moment of technological revolution, with artificial intelligence (AI) reshaping fields traditionally reliant on human cognitive abilities. This transition, driven by advancements in artificial neural networks, has transformed data processing and evaluation, creating opportunities for addressing complex and time-consuming tasks with AI solutions. Convolutional networks (CNNs) and the adoption of GPU technology have already revolutionized image recognition by enhancing computational efficiency and accuracy. In radiology, AI applications are particularly valuable for tasks involving pattern detection and classification; for example, AI tools have enhanced diagnostic accuracy and…
Citation impact
- FWCI
- 73.96
- Percentile
- 100%
- References
- 183
Authors
6Topics & keywords
- Artificial intelligence
- Computer science
- Medical imaging
- Machine learning
- Convolutional neural network
- Modalities
- Neuroimaging
- Data science
- Decent work and economic growth