Results 241 to 250 of about 36,184 (302)

The relationship between connective tissue disease and autoantibody positivity in pneumoconiosis cases. [PDF]

Medicine (Baltimore)
Akgündüz B.
europepmc   +1 more source

What Losing the National Institute for Occupational Safety and Health Means for Respiratory Health. [PDF]

Am J Respir Crit Care Med
Cummings KJ, Harrison R.
europepmc   +1 more source

Pneumoconiosis.

South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde, 1968
openaire   +1 more source

Occupational Respirable Crystalline Silica Dust Exposure and Risk of Non-Lung Cancer Mortality Among German Uranium Miners (1946-2018). [PDF]

J Occup Environ Med
Ludwig T, Kreuzer M, Taeger D, Pallapies D, Scholz-Kreisel P, Fenske N.   +5 more
europepmc   +1 more source

Development of a justification process for selecting alternative risk reduction measures. [PDF]

Front Public Health
Saik P, Tsopa V, Yavorska O, Cheberiachko S, Brezitska M, Yavorskyi A, Lozynskyi V.   +6 more
europepmc   +1 more source

Baseline characteristics from the EXCITING-ILD registry. [PDF]

BMJ Open Respir Res
Buschulte K, Kabitz HJ, Hagmeyer L, Hammerl P, Esselmann A, Wiederhold C, Skowasch D, Stolpe C, Joest M, Veitshans S, Höffgen M, Maqhuzu P, Schwarzkopf L, Hellmann A, Pfeifer M, Behr J, Karpavicius R, Guenther A, Polke M, Höger P, Somogyi V, Lederer C, Markart P, Kreuter M.   +23 more
europepmc   +1 more source

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Trends in global, regional and national incidence of pneumoconiosis caused by different aetiologies: an analysis from the Global Burden of Disease Study 2017

Occupational and Environmental Medicine, 2020
Objectives Pneumoconiosis remains a major global occupational health hazard and illness. Accurate data on the incidence of pneumoconiosis are critical for health resource planning and development of health policy. Methods We collected data for the period
Peng Shi, Shuhua Xi
exaly   +2 more sources

Potential of deep learning in assessing pneumoconiosis depicted on digital chest radiography

Occupational and Environmental Medicine, 2020
Objectives To investigate the potential of deep learning in assessing pneumoconiosis depicted on digital chest radiographs and to compare its performance with certified radiologists. Methods We retrospectively collected a dataset consisting of 1881 chest
Qiao Zhu, Jiantao Pu
exaly   +2 more sources

Pneumoconiosis incidence and prevalence among US Medicare beneficiaries, 1999-2019.

American Journal of Industrial Medicine, 2023
BACKGROUND Pneumoconiosis is a group of occupational lung diseases caused by dust and fiber exposure. This study analyzes Medicare claims to estimate the burden of pneumoconiosis among fee-for-service (FFS; Medicare Parts A and B) Medicare beneficiaries ...
L. Kurth, M. Casey, J. Mazurek, D. Blackley   +3 more
semanticscholar   +1 more source

A Fully Deep Learning Paradigm for Pneumoconiosis Staging on Chest Radiographs

IEEE journal of biomedical and health informatics, 2022
Pneumoconiosis staging has been a very challenging task, both for certified radiologists and computer-aided detection algorithms. Although deep learning has shown proven advantages in the detection of pneumoconiosis, it remains challenging in ...
Wenjian Sun, Dongsheng Wu, Yang Luo, Lu Liu, Hongjing Zhang, Shuang Wu, Yan Zhang, Chenglong Wang, Houjun Zheng, Jiang Shen, Chunbo Luo   +10 more
semanticscholar   +1 more source