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Big Data Analytics in Healthcare.

Ashwin Belle1, Raghuram Thiagarajan2, S M Reza Soroushmehr1

  • 1Emergency Medicine Department, University of Michigan, Ann Arbor, MI 48109, USA ; University of Michigan Center for Integrative Research in Critical Care (MCIRCC), Ann Arbor, MI 48109, USA.

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This summary is machine-generated.

Big data analytics is transforming healthcare research by enabling analysis of vast medical data. Challenges remain, but image, signal, and genomics analytics show promise for improving patient care.

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Area of Science:

  • Medical Informatics
  • Health Data Science

Background:

  • Big data analytics is increasingly vital in healthcare, offering tools for managing and analyzing diverse data.
  • Its application aids care delivery and disease exploration, but adoption faces significant challenges.

Purpose of the Study:

  • To discuss major challenges in big data analytics within healthcare.
  • To focus on promising areas: image, signal, and genomics-based analytics.

Main Methods:

  • Review of recent research utilizing large volumes of medical data.
  • Exploration of multimodal data integration from disparate sources.

Main Results:

  • Identified key challenges hindering big data analytics adoption in healthcare.
  • Highlighted the potential of image, signal, and genomics analytics.

Conclusions:

  • Addressing current challenges is crucial for advancing big data analytics in medicine.
  • Further research in integrated multimodal analytics can significantly impact healthcare delivery.