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Neuro Fuzzy Hybrid Models For Classification In Medical Diagnosis eBook

by Patricia Melin, Juan Carlos Guzman e German Prado-Arechiga
language: english
Publisher: Springer International Publishing, October of 2020 ‧
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This book is focused on the use of intelligent techniques, such as fuzzy logic, neural networks and bio-inspired algorithms, and their application in medical diagnosis. The main idea is that the proposed method may be able to adapt to medical diagnosis problems in different possible areas of the medicine and help to have an improvement in diagnosis accuracy considering a clinical monitoring of 24 hours or more of the patient.

In this book, tests were made with different architectures proposed in the different modules of the proposed model. First, it was possible to obtain the architecture of the fuzzy classifiers for the level of blood pressure and for the pressure load, and these were optimized with the different bio-inspired algorithms (Genetic Algorithm and Chicken Swarm Optimization). Secondly, we tested with a local database of 300 patients and good results were obtained.

It is worth mentioning that this book is an important part of the proposed generalmodel; for this reason, we consider that these modules have a good performance in a particular way, but it is advisable to perform more tests once the general model is completed.

Neuro Fuzzy Hybrid Models For Classification In Medical Diagnosis

by Patricia Melin, Juan Carlos Guzman e German Prado-Arechiga

Property Description
ISBN: 9783030604813
Publisher: Springer International Publishing
Release Date: October of 2020
Language: English
Format: eBook
File Format and Compatibility:
Collection: Springerbriefs In Applied Sciences And Technology
Categories: eBooks in English > Medicine > Orthopedics
EAN: 9783030604813
Acessibilidade: Ver características de acessibilidade indicadas pelo editor

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