Chapter 13

Future of Healthcare: Biomedical Big Data Analysis and IoMT

G. Tamiziniyan

G. Tamiziniyan

GRT Institute of Engineering and Technology, Tiruttani, Tamil Nadu, India

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A. Keerthana

A. Keerthana

Vels Institute of Science, Technology & Advanced Studies (VISTAS), Velan Nagar, P.V. Vaithiyalingam Road, Pallavaram, Chennai, Tamil Nadu, India

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First published: 10 February 2022
Citations: 1
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Summary

Biomedical big data analysis is an advanced technique exploring a plethora of datasets for extracting useful diagnostic and therapeutic information. It assists biomedical researchers to develop new algorithms and prediction models. Advancements in big data will improve the quality of diagnosis and prophylaxis. Leveraging big data analysis will reduce the challenges in healthcare ecosystem. Integration of datasets can support the healthcare providers for better patient outcomes. Big data analysis has a huge impact in personalized medicine. Development of different biomedical data repositories for medical images, biosignals and biochemistry will strengthen medical data analysis. Data collection and storage over the cloud is getting attention as the usage of wearable sensor is becoming well accepted. Cloud storage can share the information across different healthcare systems and impart possibilities for big data analytics. Internet of Things (IoT) can be used in biomedical and health monitoring applications which comprises of various biosensors and medical devices that are connected to the network. This will produce enormous data for better diagnostics and therapeutics. Physiological data of patients can be acquired using smart sensors and data can be stored in the cloud using internet. This will radically change the diagnostic approach and provide better point of care.

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