The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 29-615
Full Name: Omar M. Rijal
Position: Associate Professor
Age: ON
Sex: Male
Address: Institute of Mathematical Science, Faculty of Science, University Malaya, Lembah Pantai, 59000 Kuala Lumpur
Country: MALAYSIA
Tel: 60379674339
Tel prefix:
Fax: 60379674143
E-mail address: omarrija@um.edu.my
Other E-mails: norliza@ic.utm.my
Title of the Paper: A Relook at Logistic Regression Methods for the Initial Detection of Lung Ailments Using Clinical Data and Chest Radiography
Authors as they appear in the Paper: Omar Mohd Rijal, Mohd Iqbal, Ashari Yunus, Norliza Mohd Noor
Email addresses of all the authors: omarrija@um.edu.my, iqbal1510@gmail.com, ashdr64@yahoo.com, norliza@ic.utm.my
Number of paper pages: 10
Abstract: The problem of diagnosing patients with lung ailments such as Tuberculosis (PTB), Pneumonia (PNEU) and Lung Cancer (LC) when making their initial visit to a medical institution is the focus of this study. Clinical data involving symptoms and signs are used to make important decisions before the availability of the results of further tests. In practice, Logistic Regression Methods are frequently involved in this type of decision making. However, the problem of missing values when the numerical values of certain explanatory variables are not available persists in practical situations. In this paper a logistic regression model using four variables (age, cough, loss of weight (LOW) and loss of appetite (LOA)) are investigated for each of the three diseases. The main result of this study is that the probability of misclassifying the three disease type is large, and that good model fitting does not guarantee correct diagnosis. As a viable substitute, a graphical method !
of detection with an 85% chance of correct classification based on information extracted from the chest radiograph images is proposed.
Keywords: Statistical detection, error probability, lung disease, clinical data, chest radiography, missing values
EXTENSION of the file: .doc
Special (Invited) Session: Some Critical Remarks on the Initial Detection of Lung Ailments Using Clinical Data and Chest Radiography
Organizer of the Session: 620-499
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