scholarly journals P16‐1: Verifying performance of the deep learning algorism to detect chronic fibrosing interstitial lung diseases on chest radiograph: Assessment of detectability in each disease type

Respirology ◽  
2021 ◽  
Vol 26 (S3) ◽  
pp. 447-448
Keyword(s):  
Deep Learning ◽  
Chest Radiograph ◽  
Lung Diseases ◽  
Interstitial Lung Diseases ◽  
Disease Type

scholarly journals Deep learning in interstitial lung disease—how long until daily practice

2020 ◽  
Vol 30 (11) ◽  
pp. 6285-6292
Author(s):  
Ana Adriana Trusculescu ◽  
Diana Manolescu ◽  
Emanuela Tudorache ◽  
Cristian Oancea
Keyword(s):  
Deep Learning ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Early Diagnosis ◽  
Lung Disease ◽  
Lung Diseases ◽  
Daily Practice ◽  
Interstitial Lung Diseases ◽  
Learning Approaches ◽  
High Resolution Computed Tomography

Abstract Interstitial lung diseases are a diverse group of disorders that involve inflammation and fibrosis of interstitium, with clinical, radiological, and pathological overlapping features. These are an important cause of morbidity and mortality among lung diseases. This review describes computer-aided diagnosis systems centered on deep learning approaches that improve the diagnostic of interstitial lung diseases. We highlighted the challenges and the implementation of important daily practice, especially in the early diagnosis of idiopathic pulmonary fibrosis (IPF). Developing a convolutional neuronal network (CNN) that could be deployed on any computer station and be accessible to non-academic centers is the next frontier that needs to be crossed. In the future, early diagnosis of IPF should be possible. CNN might not only spare the human resources but also will reduce the costs spent on all the social and healthcare aspects of this deadly disease. Key Points • Deep learning algorithms are used in pattern recognition of different interstitial lung diseases. • High-resolution computed tomography plays a central role in the diagnosis and in the management of all interstitial lung diseases, especially fibrotic lung disease. • Developing an accessible algorithm that could be deployed on any computer station and be used in non-academic centers is the next frontier in the early diagnosis of idiopathic pulmonary fibrosis.

scholarly journals Identification of interstitial lung diseases using deep learning

2020 ◽  
Vol 10 (6) ◽  
pp. 6283
Author(s):  
Nidhin Raju ◽  
Anita H. B. ◽  
Peter Augustine
Keyword(s):  
Deep Learning ◽  
Medical Imaging ◽  
Lung Diseases ◽  
Medical Image Analysis ◽  
Healthcare Providers ◽  
Clinical History ◽  
Interstitial Lung Diseases ◽  
High Resolution Computed Tomography ◽  
Advanced Technique ◽  
Open Chest

The advanced medical imaging provides various advantages to both the patients and the healthcare providers. Medical Imaging truly helps the doctor to determine the inconveniences in a human body and empowers them to make better choices. Deep learning has an important role in the medical field especially for medical image analysis today. It is an advanced technique in the machine learning concept which can be used to get efficient output than using any other previous techniques. In the anticipated work deep learning is used to find the presence of interstitial lung diseases (ILD) by analyzing high-resolution computed tomography (HRCT) images and identifying the ILD category. The efficiency of the diagnosis of ILD through clinical history is less than 20%. Currently, an open chest biopsy is the best way of confirming the presence of ILD. HRCT images can be used effectively to avoid open chest biopsy and improve accuracy. In this proposed work multi-label classification is done for 17 different categories of ILD. The average accuracy of 95% is obtained by extracting features with the help of a convolutional neural network (CNN) architecture called SmallerVGGNet.

Differential diagnosis of Interstitial Lung Diseases using Deep Learning networks

2020 ◽  
Vol 68 (3) ◽  
pp. 170-178
Author(s):  
V. N. Sukanya Doddavarapu ◽  
Giri Babu Kande ◽  
B. Prabhakara Rao
Keyword(s):  
Differential Diagnosis ◽  
Deep Learning ◽  
Lung Diseases ◽  
Interstitial Lung Diseases ◽  
Learning Networks

Role of quantitative imaging and deep learning in interstitial lung diseases

2021 ◽  
Vol 8 (2) ◽  
Author(s):  
Salvatore C. FANNI ◽  
Caterina A. D’AMORE ◽  
Alessio MILAZZO ◽  
Annalisa DE LIPERI ◽  
Lucio CALANDRIELLO ◽  
...  
Keyword(s):  
Deep Learning ◽  
Lung Diseases ◽  
Quantitative Imaging ◽  
Interstitial Lung Diseases

Lung ultrasound in the evaluation of interstitial lung diseases

2016 ◽  
Vol 37 (S 01) ◽  
Author(s):  
N Buda ◽  
M Piskunowicz ◽  
M Porzezińska ◽  
W Kosiak ◽  
Z Zdrojewski
Keyword(s):  
Lung Diseases ◽  
Lung Ultrasound ◽  
Interstitial Lung Diseases

Characteristics of the immune and cytokine status in patients with interstitial lung diseases

2018 ◽  
Vol 1 (1) ◽  
pp. 25-29
Author(s):  
Mirgolib RAКHIMOV ◽  
◽  
Nematilla ARALOV ◽  
Shukhrat Ziyadullaev
Keyword(s):  
Lung Diseases ◽  
Interstitial Lung Diseases
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