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@article{175250,
        author = {Ram krishna},
        title = {Healthcare Diagnostics: A Comprehensive Review of Deep Learning and Multimodal Approaches},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2587-2590},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175250},
        abstract = {The integration of deep learning with multimodal data has revolutionized healthcare diagnostics, offering unprecedented accuracy and comprehensive insights. This review explores the advancements in deep learning-based multimodal approaches for healthcare diagnostics, encompassing diverse data types such as medical imaging, electronic health records (EHRs), genetic data, and patient demographics. By leveraging the synergistic potential of multimodal data, deep learning models can provide a holistic understanding of patient health, leading to improved diagnostic accuracy and personalized treatment plans. The review delves into key methodologies, including convolutional neural networks (CNNs) for image analysis, recurrent neural networks (RNNs) for sequential data, and transformer models for integrating heterogeneous data sources. We also discuss the challenges of multimodal data integration, such as data heterogeneity, missing data, and the need for large annotated datasets. The review highlights the latest advancements in addressing these challenges, such as transfer learning, data augmentation, and novel fusion techniques. By providing a comprehensive overview of the state-of-the-art in deep learning-based multimodal healthcare diagnostics, this review aims to guide future research and foster the development of robust, efficient, and scalable diagnostic tools, ultimately enhancing patient outcomes and advancing the field of healthcare diagnostics.},
        keywords = {Multimodal data integration, Deep learning, Healthcare diagnostics, Medical imaging, Personalized treatment},
        month = {April},
        }