International Journal of Science, Engineering and TechnologyAuthors: Asfaque Ansari, Ashutosh Upadhyay, Abhishek Kumar Singh, Aryan, Yash Raj Bhatt, Md. Iqbal
Abstract: The exponential growth of clinical documentation has created unprecedented challenges in healthcare settings. Multimodal Generative AI, leveraging both textual and structured data inputs, offers transformative solutions for automated clinical note summarization. This research paper critically examines how large language models (LLMs) and multimodal AI architectures enable efficient, accurate, and contextually relevant summarization of clinical notes. The study explores key methodologies, real-world applications, addresses critical challenges in healthcare AI implementation, and highlights future prospects in clinical documentation management. With supporting visual references and comprehensive analysis, the paper presents a detailed examination suitable for healthcare technology professionals and academic audiences, emphasizing scalability, interoperability, privacy preservation, clinical decision support, and enhanced patient-centred healthcare documentation workflows.
