This book offers readers an inside look into the field of computational analysis and deep learning in medical care. The authors include some of the leading experts in the field, who have spent years researching and developing cutting-edge technologies that are transforming the way healthcare is delivered.
The book covers a wide range of topics, including the use of machine learning algorithms and neural networks to analyze data and make predictions about patient outcomes, the development of predictive models to identify early signs of diseases and provide personalized treatment plans, and even the use of deep learning for image and speech recognition in healthcare.
Along with the technical aspects of the book, there is also a focus on ethical considerations related to the use of these technologies in medical care, as well as potential pitfalls and limitations. By
Computational Analysis and Deep Learning for Health Care: A Handbook, is a comprehensive guide for data analysts and beginners looking to explore and analyze healthcare datasets in this era of big data. This handbook will help you survive the upcoming noise of knowledge - - leveraging computational and deep learning techniques for diagnosis, treatment and how they influence health-related outcomes..
By the end of this handbook, you will know everything that you need to decide whether or not to go for a particular drug for a patient diagnosed with cancer, understand which predictors affect the cost of healthcare, and much more.
This handbook by experts in healthcare data analytics builds on concepts covered in prior editions and offers up-to-date coverage of emerging machine learning techniques such as transfer learning and low-resource machine learning.
In a clinical setting, data never lies - it reveals important insights when charted the right way. With Computational Analysis & Deep Learning, you're on a path to harness the potential of data to improve healthcare. So Grab it now!
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