Chest Radiography

Joarde, Rita; Crundwell, Neil

doi:10.1007/978-1-84882-099-9_1

Cited by 2 publications

(3 citation statements)

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“…In the present study, as opposed to previous studies ( Khan et al, 2008 ; Joarder & Crundwell, 2009 ), there was no significant relationship between drug addiction and postoperative atelectasis, which may be due to the small size of the study sample. However, like other studies ( Khan et al, 2008 ; Joarder & Crundwell, 2009 ), a great percentage of patients who were smoking and consuming alcohol had postoperative atelectasis. It is interesting that in the present study 100% of the patients who had consumed steroid medicines had postoperative atelectasis.…”

Section: Discussioncontrasting

confidence: 99%

Frequency Rate of Atelectasis in Patients Following Coronary Artery Bypass Graft and Its Associated Factors at Mazandaran Heart Center in 2013-2014

Saffari¹,

Nasiri²,

Mousavinasab³

et al. 2015

GJHS

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Introduction:As the most common postoperative pulmonary complications after cardiac surgery, atelectasis is one of the most important and serious early postoperative complications and one of the most important causes of prolonged hospitalization, increased costs, and mortality rise. Therefore, the present study was aimed at specifying the frequency of atelectasis in patients following coronary artery bypass graft and its associated factors in Mazandaran Heart Center in 2013-2014.Materials:The present investigation was a descriptive cross-sectional study in which sequential sampling was used. It was conducted on 375 patients whose coronary artery bypass graft had been performed by the same surgeon and anesthesiologist. For data collection, first the patients’ demographic variables and the information of their surgery were retrieved through their profiles, direct observation, patient inquiry, and the collected data were recorded in the data collection forms. Then, atelectasis was measured before the surgery and on the first and second days after it by taking CXR whose results were checked by two radiologists who were not aware of the previous observations. Data were analyzed through t-test, Pearson test, and Chi-square test using SPSS 16.0.Results:The results of the present study indicated that, 123 out of 375 patients (32.8%) were diagnosed with at least one type of tattletales during the first three days after the surgery. The mean age of the patients who were diagnosed with atelectasis was 62.9 and most of them were female. The results also showed that there was a significant relationship between postoperative frequency of atelectasis and the patients’ pulmonary diseases and underlying diseases like diabetes and hyperlipidemia, smoking and alcohol use before the surgery, and transfusion of 4 units of packed red blood cells during the surgery (p<0.05).Conclusion:Atelectasis is the most common postoperative complication which emerges more in patients with pulmonary and underlying diseases than other patients.

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Section: Discussioncontrasting

confidence: 99%

Frequency Rate of Atelectasis in Patients Following Coronary Artery Bypass Graft and Its Associated Factors at Mazandaran Heart Center in 2013-2014

Saffari¹,

Nasiri²,

Mousavinasab³

et al. 2015

GJHS

View full text Add to dashboard Cite

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“…Although pneumonia and most other diseases can be differentiated, X-rays are still considered as the “most challenging plain film to interpret correctly” [ 33 ]. Therefore, extracting discriminating features on CXR scans is a challenging task.…”

Section: Experiments and Resultsmentioning

confidence: 99%

“…Presently, as per our knowledge, there exists no end-to-end model that has been proposed to address the problem. If compared with CT-scans, CXR scans do not provide three-dimensional anatomy, but pneumonia and most other diseases can be differentiated, though many Radiologists consider CXR scans as “the most challenging plain film to interpret correctly” [ 33 ]. However, due to its fast imaging speed, low radiation, and low cost, X-rays are the most widely used CAD imaging modality.…”

Section: Related Workmentioning

confidence: 99%

Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network

et al. 2022

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Deep learning-based Computer-Aided Diagnosis has gained immense attention in recent years due to its capability to enhance diagnostic performance and elucidate complex clinical tasks. However, conventional supervised deep learning models are incapable of recognizing novel diseases that do not exist in the training dataset. Automated early-stage detection of novel infectious diseases can be vital in controlling its rapid spread. Moreover, development of a conventional CAD model is only possible after disease outbreak and datasets become available for training (viz. COVID-19 outbreak). Since novel diseases are unknown and cannot be included in training data, recognizing them is a challenge in existing supervised deep learning models. Even after data becomes available, recognizing new classes with conventional models requires a complete extensive re-training. The present study is the first to report this problem and propose a novel solution to it. In this study, we propose a new class of CAD models i.e., Deep-Precognitive Diagnosis, wherein artificial agents are enabled to identify unknown diseases that have potential to cause pandemic in future. A de novo biologically-inspired Conv-Fuzzy network is developed. Experimental results show that the model trained to classify chest X-ray scans into normal and bacterial pneumonia detected a novel disease during testing, unseen by it in the training sample and confirmed to be COVID-19 later. The model is also tested on SARS-CoV-1 and MERS-CoV samples as unseen diseases and achieved state-of-the-art accuracy. The proposed model eliminates the need for model re-training by creating a new class in real-time for the detected novel disease thus classifying it on all subsequent occurrences. Second, the model addresses the challenge of limited labeled data availability, which renders most supervised learning techniques ineffective and establishes that modified fuzzy classifiers can achieve high accuracy on image classification tasks.

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Chest Radiography

Cited by 2 publications

References 0 publications

Frequency Rate of Atelectasis in Patients Following Coronary Artery Bypass Graft and Its Associated Factors at Mazandaran Heart Center in 2013-2014

Frequency Rate of Atelectasis in Patients Following Coronary Artery Bypass Graft and Its Associated Factors at Mazandaran Heart Center in 2013-2014

Deep-Precognitive Diagnosis: Preventing Future Pandemics by Novel Disease Detection With Biologically-Inspired Conv-Fuzzy Network

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