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Heuristic Techniques for Real-Time Order Acceptance and Scheduling in Metal Additive Manufacturing Read chapter Read first chapter

2020 | OriginalPaper | Chapter

4. A Medical Modelling Using Multiple Linear Regression

Authors : Arshed A. Ahmad, Murat Sari, Tahir Coşgun

Published in: Mathematical Modelling and Optimization of Engineering Problems

Publisher: Springer International Publishing

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Abstract

The aim of this paper is to predict different types of pathological subjects from a population through the physical observational variables (HB, RBC, MCH, WBC, MCV, HCT, MCHC, PLT), sex, and age. To achieve this, we have used a multilinear regression model. The obtained results in terms of the proposed model are seen to be accurate enough. Thus, the regression model is expected to provide important preliminary information to the clinicians in order to plan appropriate treatment programs for their patients. This work is carried out in terms of the dataset consisting of 539 subjects provided from blood laboratories in Iraq. The resulting model is the regression model consisting of observations (the blood variables, age, and sex) and the type of anemia. Therefore, the model is developed for predicting the type of anemia to help for diagnosis of these diseases.

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Metadata
Title
A Medical Modelling Using Multiple Linear Regression
Authors
Arshed A. Ahmad
Murat Sari
Tahir Coşgun
Copyright Year
2020
Book
Mathematical Modelling and Optimization of Engineering Problems

Print ISBN: 978-3-030-37061-9

Electronic ISBN: 978-3-030-37062-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37062-6_4

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