Abstract
Huge volumes of biological and healthcare data have been generated and accumulated together rapidly with high scale. The exponential growth and easy availability of these data have offered a movement in research activity of healthcare data science. The traditional methods are incapable of processing and management of enormous quantity of complex with high-dimensional healthcare data in terms of volume and variety. Recently data science technologies have been increasingly used in the research of biomedical and healthcare informatics. Big data analytics applications have unlocked innovative opportunities to extract hidden knowledge and develop advanced computational approaches to provide improved healthcare. Computational health informatics has come as an emerging field that offers enormous research opportunities for development of computational techniques that are applicable in healthcare system. Bioinformatics also provides many computational tools and techniques to analyze huge biomolecular datasets to understand disease and enables by relating genetics and proteomics with healthcare data. This chapter presents a comprehensive review of the potential of utilizing existing computational methods including machine learning as well as deep learning technologies in healthcare sector. It also looks at the contribution of bioinformatics, healthcare informatics, and analytics in improving healthcare system.
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Meher, J. (2021). Computational Methods for Health Informatics. In: Manocha, A.K., Jain, S., Singh, M., Paul, S. (eds) Computational Intelligence in Healthcare. Health Information Science. Springer, Cham. https://doi.org/10.1007/978-3-030-68723-6_20
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