Deep learning for autism detection using clinical notes: A comparison of transfer learning for a transparent and black-box approach

This article explores the application of deep learning, specifically transfer learning, for autism detection using clinical notes. It compares transparent and black-box approaches, suggesting a focus on model explainability and potentially, the trade-offs between accuracy and interpretability. The source being ArXiv indicates this is likely a research paper, focusing on the technical aspects of the AI model and its performance.

• •Applies deep learning to a healthcare problem (autism detection).
• •Uses clinical notes as data input.
• •Compares different transfer learning approaches.
• •Focuses on model transparency and explainability.