Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions

Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions

Author
Abhishek Kumar, Ashutosh Kumar Dubey, Surbhi Bhatia, Swarn Avinash Kumar, Dac-Nhuong Le
Publisher
The Institution of Engineering and Technology
Language
English
Year
2022
Page
419
ISBN
1839535113,9781839535116
File Type
pdf
File Size
24.2 MiB

A major use of practical predictive analytics in medicine has been in the diagnosis of current diseases, particularly through medical imaging. Now there is sufficient improvement in AI, IoT and data analytics to deal with real time problems with an increased focus on early prediction using machine learning and deep learning algorithms. With the power of artificial intelligence alongside the internet of 'medical' things, these algorithms can input the characteristics/data of their patients and get predictions of future diagnoses, classifications, treatment and costs.
Evolving Predictive Analytics in Healthcare: New AI techniques for real-time interventions discusses deep learning algorithms in medical diagnosis, including applications such as Covid-19 detection, dementia detection, and predicting chemotherapy outcomes on breast cancer tumours. Smart healthcare monitoring frameworks using IoT with big data analytics are explored and the latest trends in predictive technology for solving real-time health care problems are examined. By using real-time data inputs to build predictive models, this new technology can literally 'see' your future health and allow clinicians to intervene as needed.
This book is suitable reading for researchers interested in healthcare technology, big data analytics, and artificial intelligence.

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