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- W4285141805 abstract "Big Medical Data Analytics is an intricate process of extracting information of medical interest from a massive amount of data. Unstructured or structured heterogeneous datasets gleaned from various sources are analyzed with data analytics approaches (e.g., artificial intelligence, machine learning, data mining, etc.) for excavating useful diagnostic information to predict diseases and suitable treatment models. Intensive research is needed to scrutinize the impact of big medical data analytics to diagnose cardiovascular diseases, neurological disorders, and early diagnosis of chronic and genetic diseases. Utilizing this analytics process not only shortens the decision-making time for the caregivers but initiates the development of cost-effective treatment modules, algorithms, or software-based devices. In this chapter, how big medical data analytics can be incorporated with already facilitating diagnosing diseases is discussed, as well as some analytical tools are highlighted that have higher accuracy rates compared to conventional procedures in diagnosing diseases at an early stage." @default.
- W4285141805 created "2022-07-14" @default.
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- W4285141805 date "2022-01-01" @default.
- W4285141805 modified "2023-09-30" @default.
- W4285141805 title "Big medical data analytics for diagnosis" @default.
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- W4285141805 doi "https://doi.org/10.1016/b978-0-323-91907-4.00013-3" @default.
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