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The rapid digital transformation of healthcare demands intelligent, accessible, and cost- effective diagnostic systems capable of assisting clinicians in real-time decision- making. This paper presents a Multimodal AI–Driven Smart Healthcare Platform designed to integrate medical image analysis, textual symptom understanding, and structured patient metadata into a unified diagnostic decision support framework. The proposed system employs feature-level multimodal fusion using deep learning architectures to enhance diagnostic accuracy while incorporating Explainable Artificial Intelligence (XAI) techniques to improve interpretability and clinical trust. In addition to disease prediction, the platform integrates telemedicine services, laboratory test cost optimization, digital health record management, and a real-time emergency alert mechanism.
Keywords:
Multimodal Deep Learning, Telemedicine, Explainable AI, Diagnostic Decision Support, Medical Image Classification, Healthcare Informatics.
Cite Article:
"Multimodal AI–Driven Smart Healthcare Platform for Intelligent Telemedicine and Diagnostic Decision Support", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b292-b297, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604176.pdf
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ISSN:
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