Akciğer Kanserinde Bilgisayarlı Tomografi ile Tarama: Güncel Bilgiler

Demirkazık, Figen Başaran

doi:10.5152/trs.2014.024

Cited by 2 publications

(2 citation statements)

References 26 publications

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“…The cost effectiveness of an intervention is defined as the cost required to improve the years of quality living by that intervention. [4] According to the recent studies, low-dose computed tomography is cost effective for lung screening in high-risk group, and it was reported that cost effectiveness can increase by an additional 20%-45% if smoking cessation programs are implemented. [20] In conclusion, the incidence of pathological lung findings in individuals aged more than 40 years and in workers and retired people and the incidence of emphysematous appearance in the smokers significantly increased.…”

Section: Discussionmentioning

confidence: 99%

“…[3] As in developed countries, lung cancer is the leading cause of cancer-related death in our country as well. [4] Lung cancer can be divided into two main histopathological subtypes: small-cell lung cancer (25%) and non-small-cell lung cancer (75%). [5] While 50%-60% of lung cancers are detected as parenchymal nodule or mass, 40%-50% of them are detected as central endobronchial, hilar, or mediastinal mass.…”

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A Cross-sectional Study in Konya; 2,015 Evaluation of Lung Graph

Alkan

Tolu

İnal³

et al. 2017

EJMO

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E pidemiological studies, which are defined as the examination of the incidence of diseases in society and the factors affecting it, are aimed to reveal the incidence and causes of the disease, to eliminate the disease agents, and to manage the resources efficiently and correctly. [1] Posteroanterior (PA) chest radiograph, one of the earliest practical methods used to detect thoracic pathologies, is used in imaging the trachea, mediastinum, the heart, the diaphragm, subdiaphragmatic areas, hilus, pulmonary vasculature, fissures, sinuses, lung parenchyma, pleura, soft Objectives: This study was an evaluation of posteroanterior chest radiographs taken of residents of Konya determined by the cluster sampling method. Methods: This study was a descriptive cross-sectional study, conducted in cooperation with the Konya Education and Research Hospital, the provincial health directorate, and the metropolitan municipality. The sociodemographic characteristics of 2015 individuals participating in the study were recorded. The standard chest radiographs, which were taken with a traditional analog system during inspiration in the standing position, were evaluated by 2 radiologists. The most obvious pathological finding was recorded. Results: Of the participants, 1075 (53.40%) were female and 940 (46.60%) were male. The mean age was 45.89±0.45 years for the women and 46.20±0.54 years for the men. In the group, 340 (16.90%) were retired, 492 (24.40%) were farmers and/or laborers, 144 (7.10%) were white-collar employees, and 1039 (51.60%) were housewives or unemployed. In all, 580 (28.80%) were cigarette smokers. While 249 (12.36%) had pathological findings on the chest radiograph, 1766 (87.64%) had normal results. The pathological findings were hilar fullness (n=50, 2.48%), emphysematous appearance (n=48, 2.38%), nodule (n=29, 1.44%), increased reticulonodular density (n=26, 1.29%), increased bronchovascular branching (n=9, 0.44%), bronchiectasis (n=4, 0.20%), and other changes (n=83, 4.12%). The incidence of emphysematous appearance was 2.77 times greater in the smokers than in the non-smokers (p<0.05; odds ratio [OR]: 2.77, confidence interval [CI]: 1.56-4.91). While the chest X-ray was normal in 93.50% of the individuals under the age of 40 years, the rate decreased to 84.60% in the individuals over the age of 40 years. The incidence of a pathological chest radiograph was also 2.62 times higher in individuals over the age of 40 years (p<0.001; OR: 2.62, CI:1.90-3.61). Conclusion:The incidence of pathological lung findings was greater in individuals over the age of 40 years, and in workers and retirees.

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confidence: 99%

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confidence: 99%

A Cross-sectional Study in Konya; 2,015 Evaluation of Lung Graph

Alkan

Tolu

İnal³

et al. 2017

EJMO

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The Effect of Hyper Parameters on the Classification of Lung Cancer Images Using Deep Learning Methods

NARİN

Onur

2022

Erzincan Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Cancer is a fatal disease arised from the formation of abnormal cells as a result of random growth in the human body. Lung cancer is the frequently encountered cancer type and causes abnormal growth of lung cells. Diagnosis at an early stage substantially enhances the chance of survivability of the patient, as well as prolongs the survival time. There may even be a complete recovery. For this reason, it is of vital importance to support the diagnosis and detection of doctors and enables them to diagnose more easily and quickly. In this paper, it is aimed to detect lung cancer disease with the help of Alexnet and Resnet50 architectures, which are deep learning architectures, by using computed tomography images. In addition, the performances of the hyper-parameters of maximum epoch and batch size, which are of great importance in training the models, have been compared. According to the results obtained, the highest overall accuracy in automatic detection of lung cancer has been achieved with the AlexNet architecture. The highest overall accuracy value obtained as a result of the simulations is found to be 98.58% with the highest cycle value and the batch size are 200 and 64, respectively.

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Akciğer Kanserinde Bilgisayarlı Tomografi ile Tarama: Güncel Bilgiler

Cited by 2 publications

References 26 publications

A Cross-sectional Study in Konya; 2,015 Evaluation of Lung Graph

A Cross-sectional Study in Konya; 2,015 Evaluation of Lung Graph

The Effect of Hyper Parameters on the Classification of Lung Cancer Images Using Deep Learning Methods

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