Faculty Opinions recommendation of Not following the rules in guideline care for lung cancer diagnosis and staging has negative impact.

2020 ◽  
Author(s):  
Paul Van Schil
Keyword(s):  
Lung Cancer ◽  
Cancer Diagnosis ◽  
Negative Impact ◽  
Lung Cancer Diagnosis ◽  
Guideline Care

Not Following the Rules in Guideline Care for Lung Cancer Diagnosis and Staging Has Negative Impact

2020 ◽  
Vol 110 (5) ◽  
pp. 1730-1738
Author(s):  
Candice L. Wilshire ◽  
Joshua R. Rayburn ◽  
Shu-Ching Chang ◽  
Christopher R. Gilbert ◽  
Brian E. Louie ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Diagnosis ◽  
Negative Impact ◽  
Lung Cancer Diagnosis ◽  
Guideline Care

scholarly journals Venous and Lung Thromboembolism in the Context of Lung Cancer: Clinical Manifestations, Risk Factors and Prognosis

2019 ◽  
Vol 32 (10) ◽  
pp. 647 ◽  
Author(s):  
Rosana Maia ◽  
Inês Neves ◽  
António Morais ◽  
Henrique Queiroga
Keyword(s):  
Lung Cancer ◽  
Venous Thromboembolism ◽  
Cancer Diagnosis ◽  
Negative Impact ◽  
Clinical Manifestations ◽  
Research Subjects ◽  
Lung Cancer Diagnosis ◽  
The Impact ◽  
The Relationship

Introduction: The relationship between cancer and thromboembolic events has been known for a long time. Lung and venous thromboembolism are frequent complications of lung cancer and its treatment, being a great cause of morbidity and mortality. We pretend to establish the relationship between lung and venous thromboembolism and lung cancer, describe patient characteristics and analyze the impact in the survival and prognosis.Material and Methods: It was a retrospective study. All research subjects were selected from lung cancer patients with a newly diagnosed lung and venous thromboembolism event admitted to Hospital S. João, between January 2008 and December 2013 and were followed until December 2014. Statistical analysis was performed with SPSS.Results: From the search, we obtained 113 patients. The majority was male, smokers or ex-smokers, and adenocarcinoma was the most frequent histologic type, being diagnosed mostly in advanced stages. We noticed that the median time between lung cancer diagnosis and lung venous thromboembolism was 2.9 months. In 24 patients (21.4%), the lung cancer diagnosis occurred after the lung and venous thromboembolism event and in 86 patients (76.8%), it occurred before the event. After a median follow up of 1.4 months, 107 (94.7%) patients died, 1 (0.9%) was lost to follow-up and 5 (4.4%) were still alive. The median survival rate was 1.5 months.Discussion: The diagnosis of lung and venous thromboembolism in patients with lung cancer is associated with bad prognosis. It occurs most frequently in patients with advanced disease, in the first months after lung cancer diagnosis and after beginning chemotherapy.Conclusion: Disease progression is an independent predictor with negative impact in overall survival.

Computer-Aided Lung Cancer Diagnosis Approaches Based on Deep Learning

2018 ◽  
Vol 30 (1) ◽  
pp. 90 ◽  
Author(s):  
Peng Zhang ◽  
Xinnan Xu ◽  
Hongwei Wang ◽  
Yuanli Feng ◽  
Haozhe Feng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Deep Learning ◽  
Cancer Diagnosis ◽  
Lung Cancer Diagnosis ◽  
Computer Aided

Biased Lung Cancer Risk Perceptions: Smokers are Misinformed

2018 ◽  
Vol 238 (5) ◽  
pp. 395-421 ◽  
Author(s):  
Nicolas R. Ziebarth
Keyword(s):  
Lung Cancer ◽  
Cancer Risk ◽  
Cancer Diagnosis ◽  
Mortality Risk ◽  
Risk Perceptions ◽  
Lung Cancer Risk ◽  
Lifetime Risk ◽  
Lung Cancer Diagnosis ◽  
Cancer Risk Perceptions ◽  
Overall Mortality

Abstract This paper empirically investigates biased beliefs about the risks of smoking. First, it confirms the established tendency of people to overestimate the lifetime risk of a smoker to contract lung cancer. In this paper’s survey, almost half of all respondents overestimate this risk. However, 80% underestimate lung cancer deadliness. In reality, less than one in five patients survive five years after a lung cancer diagnosis. Due to the broad underestimation of the lung cancer deadliness, the lifetime risk of a smoker to die of lung cancer is underestimated by almost half of all respondents. Smokers who do not plan to quit are significantly more likely to underestimate this overall mortality risk.

scholarly journals An Efficient DA-Net Architecture for Lung Nodule Segmentation

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1457
Author(s):  
Muazzam Maqsood ◽  
Sadaf Yasmin ◽  
Irfan Mehmood ◽  
Maryam Bukhari ◽  
Mucheol Kim
Keyword(s):  
Computed Tomography ◽  
Lung Cancer ◽  
Ct Scan ◽  
Cancer Diagnosis ◽  
Lung Nodule ◽  
Search Space ◽  
Lung Nodules ◽  
Suggested Model ◽  
Lung Cancer Diagnosis ◽  
Segmentation Framework

A typical growth of cells inside tissue is normally known as a nodular entity. Lung nodule segmentation from computed tomography (CT) images becomes crucial for early lung cancer diagnosis. An issue that pertains to the segmentation of lung nodules is homogenous modular variants. The resemblance among nodules as well as among neighboring regions is very challenging to deal with. Here, we propose an end-to-end U-Net-based segmentation framework named DA-Net for efficient lung nodule segmentation. This method extracts rich features by integrating compactly and densely linked rich convolutional blocks merged with Atrous convolutions blocks to broaden the view of filters without dropping loss and coverage data. We first extract the lung’s ROI images from the whole CT scan slices using standard image processing operations and k-means clustering. This reduces the search space of the model to only lungs where the nodules are present instead of the whole CT scan slice. The evaluation of the suggested model was performed through utilizing the LIDC-IDRI dataset. According to the results, we found that DA-Net showed good performance, achieving an 81% Dice score value and 71.6% IOU score.

The efficacy of Raman spectroscopy in lung cancer diagnosis: the first diagnostic meta-analysis

2021 ◽  
Author(s):  
Zhang-Yan Ke ◽  
Ya-Jing Ning ◽  
Zi-Feng Jiang ◽  
Ying-ying Zhu ◽  
Jia Guo ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Raman Spectroscopy ◽  
Cancer Diagnosis ◽  
Meta Analysis ◽  
Lung Cancer Diagnosis
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