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Newer models like JAGAN (Joint Attention Generative Adversarial Nets) are introduced to ensure that the generated text maintains a professional "clinical language style". 📊 Key Challenges & Metrics

Traditional training data can lead to hallucinations or biased outputs, particularly in socio-economically diverse content. 126287

“Despite the great progress made by existing deep generation methods, it is still inadequate in (1) insufficient consideration of the visual-pathological gap and (2) weak evaluation of clinical language style.” National Institutes of Health (.gov) · 4 months ago Metrics like BLEU and ROUGE are used to

The identifier refers to the specific article index for a prominent scientific review titled "Deep image captioning: A review of methods, trends and future challenges" , published in the journal Neurocomputing (Volume 546, August 2023). 🏥 Focus on Medical Report Generation

Metrics like BLEU and ROUGE are used to measure accuracy, but they sometimes struggle to capture the full semantic meaning or clinical relevance of a caption.

This review provides a systematic and comprehensive analysis of how deep learning models translate visual content into human language, with a particular focus on both general and medical applications. 🔬 Core Components of the Review

Translating those visual features into coherent text using architectures like RNNs, LSTMs, and Transformers. 🏥 Focus on Medical Report Generation