Foundations of AI in Radiology: From CNNs to Multimodal Models

Understanding AI fundamentals helps radiologists evaluate and implement AI. This review covers convolutional neural networks, U-Nets, vision transformers, and vision-language models for multimodal clinical decision support, plus challenges in validation, bias, and regulation.

• AI is evolving from image reconstruction to multimodal clinical decision support.
• Convolutional neural networks, U-Nets, and vision transformers are key architectures radiologists should understand.
• Challenges like bias, generalizability, and regulation demand radiologist involvement for safe implementation.

Automated summary

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