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May 20, 2026Iraqi Journal for Computers and InformaticsOpen Access

Multimodal Deep Learning in Healthcare Recommender Systems: A Review of CNN-Based Architectures

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Authors

HTHikmat TaherMAMaha S. AbdulridhaRGRana M. Ghadban

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Overview

Review investigates CNN-based architectures in healthcare recommender systems, suggesting new methodologies and challenges.

Key Points

  • The review aims to explore CNN-based architectures for healthcare recommender systems and their integration with other recommendation methods.
  • Analyzed CNN-based architectures in healthcare recommender systems.
  • Discussed hybrid recommendation techniques and multimodal fusion methods.
  • Reviewed new developments like vision–language models and federated learning.
  • Highlighted methodological advances in CNN-based systems.
  • Identified challenges including generalization and clinical integration.
  • Provided insights into ethical considerations for system designs.

Cite This Study

Taher et al. (2026) studied this question.

synapsesocial.com/papers/6a0d4e9df03e14405aa99d04https://doi.org/10.25195/ijci.v52i1.744
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  3. 3A Review of Deep Learning Algorithms and Their Applications in Healthcare2026
  4. 4Enhancing Healthcare Predictions with Deep Learning Models2024 · 1 citations
  5. 5Rethinking Convolutional Neural Network in Multimodal Sequential Recommendation2025