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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21574
Article Published : 8528
Total Authors : 22430
Total Reviewer : 805
Total Countries : 159
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| Paper Title: | Multimodal Disease Prediction using Deep Learning |
| Authors Name: | Harika Thalla , Kopalle Laxmi Meenakshi , B.N.S.L.Rajeshwari Renu |
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IJRTI_207867
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| Published Paper Id: | IJRTI2511140 |
| Published In: | Volume 10 Issue 11, November-2025 |
| DOI: | |
| Abstract: | Chest X-rays are amongst the most commonly used tools for diagnosing lung and chest-related diseases. Manual interpretation is often time-consuming and prone to human error due to subtle variations in image patterns. So to overcome these limitations, we are proposing a deep learning model for automatic disease detection using the Chest X-ray dataset. The research begins with a simple Convolutional Neural Network model and gradually advances toward more complex architectures like CheXNet and DenseNet-121, for accurate medical imaging. To support the AI model results, explainability is used to highlight the regions that influence the model’s decisions, that is GradCAM is used, by providing clear explanations for each prediction. This makes the model accurate and also interpretable for medical practitioners. The system shows promising results in identifying multiple chest abnormalities efficiently. For the future scope, the model can be expanded by including patient metadata such as symptoms and demographic details to enhance diagnostic precision. Early and explainable detection of thoracic diseases can support doctors to make faster and more reliable medical decisions.Overall, the proposed approach bridges the gap between deep learning and explainability , contributing to trustworthy and accessible AI-based healthcare. |
| Keywords: | Chest X-ray, Deep Learning, CheXNet, DenseNet-121, Explainable Artificial Intelligence, Grad-CAM |
| Cite Article: | "Multimodal Disease Prediction using Deep Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 11, page no.b317-b326, November-2025, Available :http://www.ijrti.org/papers/IJRTI2511140.pdf |
| Downloads: | 000203 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2511140
Registration ID:207867
Published In: Volume 10 Issue 11, November-2025
DOI (Digital Object Identifier):
Page No: b317-b326 Country: hyderabad, telangana, india Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2511140 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2511140 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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