Abstract
In this day and age, Artificial Intelligence has crept into every domain of work. It is only fitting that it be made a part of the medical domain as well. With the vast amount of healthcare data available in various forms such as image, video, text, and due to emerging technologies and advancements in data science, tools are being created to ease the process of medical analysis and provide an efficient and accurate diagnosis of the patient. Such techniques save lots of human efforts and provide a rather accurate result. In particular, the chapter focuses on emphasizing the importance of multimodal system where instead of relying on a particular data source or a particular field of data analytics; one can combine multiple sources and apply multi-domain techniques to extract information to an even greater extent. The high-quality information retrieved from the analysis can be further used to determine and diagnose more symptoms and hence help in providing accurate solutions.
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Hiriyannaiah, S. et al. (2021). Multi-modal Data-Driven Analytics for Health Care. In: Srinivasa, K.G., G. M., S., Sekhar, S.R.M. (eds) Artificial Intelligence for Information Management: A Healthcare Perspective. Studies in Big Data, vol 88. Springer, Singapore. https://doi.org/10.1007/978-981-16-0415-7_7
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