Enhancing Diagnostic Accuracy and Reducing Diagnostic Delays through Multi-Modal Data Fusion in Next-Generation Clinical Information Systems
Keywords:
Multi-modal data fusion, Diagnostic accuracy, Clinical decision support systems, Healthcare AI, Medical informatics, Data integrationAbstract
The integration of multi-modal data fusion (MMDF) within next-generation clinical information systems (NGCIS) is revolutionizing medical diagnostics by enhancing accuracy and reducing delays. By merging diverse data types — such as imaging, genomic, clinical, and sensor data — MMDF enables a more holistic view of patient health. This paper explores the evolution of MMDF approaches, highlights current challenges, and proposes a framework for embedding MMDF into clinical decision support systems (CDSS). Our review indicates significant improvements in early diagnosis, treatment planning, and outcomes through MMDF. Future developments must address data standardization, interoperability, and ethical implications to fully realize the potential of NGCIS.
References
Zhang, Y., Sheng, M., Liu, X., Wang, R., Lin, W. (2022). A heterogeneous multi-modal medical data fusion framework. Health Information Science and Systems, 10(1), 17–33.
Kumar, A. (2022). Deep learning for multi-modal medical imaging fusion. International Journal of Engineering Technology Research & Management, 9(2), 45–58.
Cui, C., Yang, H., Wang, Y., Zhao, S., Asad, Z. (2023). Deep multimodal fusion in disease diagnosis. Progress in Biomedical Engineering, 5(1), 015001.
Wu, Y., Chen, J., Hu, L., Xu, H., Liang, H. (2024). OmniFuse: Modality fusion on low-quality data. Information Fusion, 98, 103186.
Choi, A., Lee, K., Hyun, H., Kim, K.J., Lee, K.H. (2024). DL-based real-time deterioration prediction. Scientific Reports, 14, 2678.
Wang, Z., Lin, R., Li, Y., Zeng, J., Chen, Y. (2024). Multi-modal integration for breast cancer survival prediction. Precision Clinical Medicine, 7(2), pbae012.
Duan, J., Xiong, J., Li, Y., Ding, W. (2024). Multimodal biomedical fusion review. Information Fusion, 97, 103165.
Huang, Y., Huang, X., Wang, A., Chen, Q., Chen, G. (2023). Decision models based on MMDF. BMC Medical Informatics and Decision Making, 23, 157.
Amir, A., Beymer, D., Grace, J., Greenspan, H. (2010). AALIM: Cardiac CDSS. MEDINFO 2010, 846–850.
Morís, D.I., Moura, J., Marcos, P.J., Rey, E.M., Novo, J. (2024). COVID-19 case study with MMDF. Heliyon, 10(3), e14673.
Hayat, N., Geras, K.J., Shamout, F.E. (2022). MedFuse: Clinical + imaging time-series. ML Research, 182, 1–11.
Madabhushi, A., Agner, S., Basavanhally, A. (2011). CAD prognosis with multi-scale fusion. Computerized Medical Imaging and Graphics, 35(3), 200–208.
Lee, K., Lee, K.H., Kim, K.J., Hyun, H. (2024). ED deterioration prediction model. Scientific Reports, 14, 2745.
