Decision-Making Using Big Data in Predicting Degenerative Diseases

V. Bhanumathi () and C. P. Sangeetha
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V. Bhanumathi: Anna University, Regional Campus
C. P. Sangeetha: Anna University, Regional Campus

Chapter Chapter 4 in The Digitalization Conundrum in India, 2020, pp 53-71 from Springer

Abstract: Abstract The applications of Wireless Body Area Networks (WBAN) are numerous concerning medical field like continuous health monitoring of old age people; post-surgical monitoring; prediction of degenerative diseases like cancer, tumour, heart disease, Alzheimer, dementia, etc. The term ‘Big Data’ is now playing a decisive role in medical applications in analysing the patient disease to support the medical practitioner in making a wise diagnosis. By going through the long-term data, he can easily provide immediate and effective healthcare solutions. The continuous monitoring of the physiological parameters, such as sugar level, heartbeat, respiration rate, etc., will result in a big volume of data. Hence, it can be said that the big data analytics along with the emerging Internet of Things (IoT) technology will help the concerned person to work and make decisions efficiently in eHealth and mHealth medical scenarios. This chapter concentrates on defining decision-making architecture for the degenerative disease, Alzheimer’s disease named Alzheimer's Health Management and Analysis (AHMA), with the help of sensors, big data and IoT. The degenerative disease is one which will kill a man over a long run and the symptoms will not be known in advance. With this growing technology, disease analytics are becoming easier and it saves time in analysing the patients. Because these patients cannot be interviewed for a longer duration, the big data derived from the system will be very much beneficial for making decisions.

Date: 2020
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DOI: 10.1007/978-981-15-6907-4_4

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