Indian Journal of Occupational and Environmental Medicine: Table of Contents

Official publication of Indian Association of 0ccupational Health

Users Online:443

IAOH | Subscription | e-Alerts | Feedback | Login

About us

Article Cited by others

REVIEW ARTICLE

Using spirometry results in occupational medicine and research: Common errors and good practice in statistical analysis and reporting

Wagner N L, Beckett W S, Steinberg R

Year : 2006| Volume: 10| Issue : 1 | Page no: 5-10

This article has been cited by

1	PULMONARY FUNCTION TESTS OF FEMALES WORKING AT CONSTRUCTION SITES

	Neera Goel, Niraj Kumar Yadav

	Journal of Evolution of Medical and Dental Sciences. 2018; 7(18): 2246

	[Pubmed] [Google Scholar] [DOI]

2	A 2-year follow-up of spirometric parameters in workers of a tile and ceramic industry, Yazd, southeastern Iran

	Mehrparvar, A.H. and Mirmohammadi, S.J. and Mostaghaci, M. and Davari, M.H. and Hashemi, S.H.

	International Journal of Occupational and Environmental Medicine. 2013; 4(2): 73-79

	[Pubmed] [Google Scholar]

3	Work related respiratory symptoms and pulmonary function tests observed among construction and sanitary workers of Thoothukudi

	Mariammal, T. and Amutha Jaisheeba, A. and Sornaraj, R.

	International Journal of PharmTech Research. 2012; 4(3): 1266-1273

	[Pubmed] [Google Scholar]

4	Effect of occupational exposure to dust on pulmonary function in workers associated with building demolition

	Smilee, J.S. and Ajay, K.T. and Dhanyakumar, G. and Prabhu, R.N. and Vivian, S.T.

	Biomedical Research. 2011; 22(2): 241-247

	[Pubmed] [Google Scholar]

5	Evaluation of flow - Volume spirometric test using neural network based prediction and principal component analysis

	Kavitha, A. and Sujatha, M. and Ramakrishnan, S.

	Journal of Medical Systems. 2011; 35(1): 127-133

	[Pubmed] [Google Scholar]

6	Evaluation of Flow–Volume Spirometric Test Using Neural Network Based Prediction and Principal Component Analysis

	Anandan Kavitha,Manoharan Sujatha,Swaminathan Ramakrishnan

	Journal of Medical Systems. 2011; 35(1): 127

	[Pubmed] [Google Scholar] [DOI]

7	Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression

	A. Kavitha,C. Sujatha,S. Ramakrishnan

	Measurement Science Review. 2010; 10(2)

	[Pubmed] [Google Scholar] [DOI]

8	Prediction of spirometric forced expiratory volume (FEV 1) data using support vector regression

	Kavitha, A. and Sujatha, C.M. and Ramakrishnan, S.

	Measurement Science Review. 2010; 10(2): 63-67

	[Pubmed] [Google Scholar]

9	Predictive equations for lung function based on a large occupational population in North China

	Wu, Y., Zhang, Z., Gang, B., Love, E.J.

	Journal of Occupational Health. 2009; 51(6): 471-477

	[Pubmed] [Google Scholar]