Electronic Resource

Neuro Fuzzy Hybrid Models for Classification in Medical Diagnosis

---

Penilaian

---

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 general model; 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.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
1908000821	EB0001401	610.285 63 Mel n	Central Library (OPAC)	Available

Detail Information

Series Title

SpringerBriefs in Applied Sciences and Technology

Call Number

610.285 63 Mel n

Publisher

Switzerland : Springer Cham., 2020

Collation

ix, 103p.:Ill

Language

English

ISBN/ISSN

978-3-030-60481-3

Classification

610.285 63

Content Type

Ebook

Media Type

-

Carrier Type

online resource

Edition

1

Subject(s)

Artificial intelligence--Medical applications

Specific Detail Info

-

Statement of Responsibility

BRF

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment