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.