JMIR Publications

ABSTRACT

Abstract Multimodal data integration has emerged as a transformative approach in the healthcare sector, significantly enhancing the diagnosis, treatment, and management of various medical conditions. This review explores the development and challenges of multimodal integration, with a focus on its applications across different disease domains, particularly in oncology and ophthalmology. Multimodal integration combines data from genomics, imaging, electronic health records, and wearable devices to provide a comprehensive understanding of a patient's health status. For instance, in oncology, the integration of genomic data with imaging and clinical records enables more precise tumor characterization and personalized treatment plans. In ophthalmology, multimodal integration through the combination of genetic testing, optical coherence tomography (OCT), and fluorescein angiography data facilitates the early diagnosis of retinal diseases. The review also highlights the future directions of multimodal integration, including its expanded applications such as neurological and otolaryngological diseases, and the trend towards large-scale multimodal models, which enhance accuracy and accessibility. These approaches aid in analyzing complex and diverse datasets, thereby improving healthcare outcomes. We also summarize the current challenges faced in this field. Overall, the innovative potential of multimodal integration is expected to further revolutionize the healthcare industry, providing more comprehensive and personalized solutions for disease management.