# bib

id: cord-297198-dneycnyr
author: Khan, T.
date: 2020-05-27
extension: .txt
mime: text/plain
words: 645
sentence: 30
flesch: 60
cache: cache/cord-297198-dneycnyr.txt
txt: txt/cord-297198-dneycnyr.txt
title:
  Re: a British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic

summary:
  In addition, a more recent study by Wong et al. reported abnormal CXR in 44/64 (68.8%) of COVID-19 patients on presentation 4 ; however, it is important to note that both of these studies included hospitalised patients, representing individuals with more severe illness. The study of Guan et al., also cited by Nair et al., reported CXR abnormalities in only 162/274 (59.1%) of COVID-19 patients.


id: cord-350636-ufwfitue
author: Shumilov, Evgenii
title: Comparison of Chest Ultrasound and Standard X-Ray Imaging in COVID-19 Patients
date: 2020-09-02
extension: .txt
mime: text/plain
words: 2371
sentence: 99
flesch: 42
cache: cache/cord-350636-ufwfitue.txt
txt: txt/cord-350636-ufwfitue.txt
summary:
  We aimed to investigate patterns of ChUS in COVID-19 patients and compare the findings with results from chest X-ray (CRX). ChUS was especially useful to detect interstitial syndrome compared to CXR in COVID-19 patients (17/18 vs. 11/18; p<0.02).


id: cord-028786-400vglzm
author: Oloko-Oba, Mustapha
title: Diagnosing Tuberculosis Using Deep Convolutional Neural Network
date: 2020-06-05
extension: .txt
mime: text/plain
words: 2438
sentence: 100
flesch: 41
cache: cache/cord-028786-400vglzm.txt
txt: txt/cord-028786-400vglzm.txt
summary:
  Chest radiography in tuberculosis detection: summary of current WHO recommendations and guidance on programmatic approaches Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks Can tuberculosis patients in resource-constrained settings afford chest radiography? In: Computer-Aided Diagnosis TX-CNN: detecting tuberculosis in chest X-ray images using convolutional neural network Testing for tuberculosis Discriminative feature extraction from X-ray images using deep convolutional neural networks Deep-learning: a potential method for tuberculosis detection using chest radiography Detecting tuberculosis in radiographs using combined lung masks Combination of texture and shape features to detect pulmonary abnormalities in digital chest X-rays Automatic detection of abnormalities in chest radiographs using local texture analysis A hybrid knowledgeguided detection technique for screening of infectious pulmonary tuberculosis from chest radiographs Fusion of local and global detection systems to detect tuberculosis in chest radiographs A survey on image data augmentation for deep learning


id: cord-337507-cqbbrnku
author: Cozzi, Andrea
title: Chest x-ray in the COVID-19 pandemic: Radiologists’ real-world reader performance
date: 2020-09-10
extension: .txt
mime: text/plain
words: 2600
sentence: 71
flesch: 33
cache: cache/cord-337507-cqbbrnku.txt
txt: txt/cord-337507-cqbbrnku.txt
summary:
  The increase in accuracy over time strengthens CXR role as a first line examination in suspected COVID-19 patients. Such data play in favour of the use of CXR as first line examination when chest imaging is required in suspected COVID-19 patients during a pandemic peak.


id: cord-331891-a6b1xanm
author: Cozzi, Diletta
date: 2020-06-09
extension: .txt
mime: text/plain
words: 2919
sentence: 123
flesch: 43
cache: cache/cord-331891-a6b1xanm.txt
txt: txt/cord-331891-a6b1xanm.txt
title:
  Chest X-ray in new Coronavirus Disease 2019 (COVID-19) infection: findings and correlation with clinical outcome

summary:
  Analysis of Variance (ANOVA) was performed to detect possible differences among RALE score estimated in the following groups: discharged patients, hospitalized patients into a medicine department, hospitalized patients into an ICU (respectively, group 1, 2 and 3 in the following). It is operationally much 2 Box and Whisker plot of RALE score estimated in each group defined by outcome: discharged patients (group 1), hospitalized patients into a medicine department (group 2), hospitalized patients into an intensive care unit (group 3).


id: cord-266672-t85wd0xq
author: Bagnera, Silvia
date: 2020-07-20
extension: .txt
mime: text/plain
words: 3064
sentence: 102
flesch: 38
cache: cache/cord-266672-t85wd0xq.txt
txt: txt/cord-266672-t85wd0xq.txt
title:
  Performance of Radiologists in the Evaluation of the Chest Radiography with the Use of a “new software score” in Coronavirus Disease 2019 Pneumonia Suspected Patients

summary:
  The average time for obtaining the result with the automatic software was between 7 s (e.g., zero COVID-19 score) and 21 s (e.g., with COVID-19 score from 6 to 12). In fact, the class with COVID-19 score from 0 to 4 correlates with negative imaging and pauci-symptomatic patient.


id: cord-345528-rk16pt0i
author: Yasar, Y.
date: 2020-05-08
extension: .txt
mime: text/plain
words: 3174
sentence: 154
flesch: 53
cache: cache/cord-345528-rk16pt0i.txt
txt: txt/cord-345528-rk16pt0i.txt
title:
  MantisCOVID: Rapid X-Ray Chest Radiograph and Mortality Rate Evaluation With Artificial Intelligence For COVID-19

summary:
  From top to bottom, original CXR PA images, annotated images via experts, AI examination results respectively Infectious Diseases Society of America/American Thoracic Society consensus guidelines on the management of community-acquired pneumonia in adults Frequency and distribution of chest radiographic findings in COVID-19 positive patients. The first model is generated to classify whether the input image is x-ray image or not.


id: cord-310228-bqpvykce
author: Borkowski, A. A.
title: Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis
date: 2020-05-26
extension: .txt
mime: text/plain
words: 3194
sentence: 150
flesch: 44
cache: cache/cord-310228-bqpvykce.txt
txt: txt/cord-310228-bqpvykce.txt
summary:
  In addition, we describe the creation of a publicly available website that could augment COVID-19 pneumonia CXR diagnosis. 24 Most of the literature evaluating radiographs of COVID-19 patients .


id: cord-297396-r1p7xn3a
author: Ng, Ming-Yen
title: Development and Validation of Risk Prediction Models for COVID-19 Positivity in a Hospital Setting
date: 2020-09-15
extension: .txt
mime: text/plain
words: 3254
sentence: 136
flesch: 47
cache: cache/cord-297396-r1p7xn3a.txt
txt: txt/cord-297396-r1p7xn3a.txt
summary:
  Reverse transcription polymerase chain reaction (RT-PCR) is regarded as a vital tool in identifying the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and quarantining COVID-19 patients to prevent further spread of the disease 4 . As yet, the data which supports these strategies are predominantly based on data of COVID-19 patients 12, 13 but without comparisons to patients with other conditions and symptoms overlapping with COVID-19 (eg. fever, shortness of breath, cough).


id: cord-282198-ugmv9om1
author: Pare, Joseph R.
title: Point-of-care Lung Ultrasound Is More Sensitive than Chest Radiograph for Evaluation of COVID-19
date: 2020-06-19
extension: .txt
mime: text/plain
words: 3411
sentence: 160
flesch: 48
cache: cache/cord-282198-ugmv9om1.txt
txt: txt/cord-282198-ugmv9om1.txt
summary:
  Further work may find LUS for the evaluation and care of COVID-19 patients to be of clinical benefit and may also have a role to guide testing as screening and contact tracing are expanded. acr.org/Advocacy-and-Economics/ACR-Position-Statements/ Recommendations-for-Chest-Radiography-and-CT-for-Suspected-COVID19-Infection Frequency and distribution of chest radiographic findings in COVID-19 positive patients Accuracy of lung ultrasonography versus chest radiography for the diagnosis of adult community-acquired pneumonia: review of the literature and meta-analysis Can lung US help critical care clinicians in the early diagnosis of novel coronavirus (COVID-19) pneumonia? Findings of lung ultrasonography of novel corona virus pneumonia during the 2019-2020 epidemic A preliminary study on the ultrasonic manifestations of peripulmonary lesions of non-critical novel coronavirus pneumonia (COVID-19) Diagnosing acute heart failure in the emergency department: a systematic review and metaanalysis Guidelines for Reporting Diagnostic Accuracy Studies: explanation and elaboration Relevance of lung ultrasound in the diagnosis of acute respiratory failure: the BLUE protocol What's new in lung ultrasound during the COVID-19 pandemic Transforming growth factor beta-1 as a predictor of fibrosis in tuberculous pleurisy Pulmonary imaging of pandemic influenza H1N1 infection: relationship between clinical presentation and disease burden on chest radiography and CT A coefficient of agreement for nominal scales


id: cord-006708-nionk55w
author: Aktaş, Fatma
title: The pulmonary findings of Crimean–Congo hemorrhagic fever patients with chest X-ray assessments
date: 2019-03-25
extension: .txt
mime: text/plain
words: 3585
sentence: 185
flesch: 53
cache: cache/cord-006708-nionk55w.txt
txt: txt/cord-006708-nionk55w.txt
summary:
  key: cord-006708-nionk55w authors: Aktaş, Fatma; Aktaş, Turan title: The pulmonary findings of Crimean–Congo hemorrhagic fever patients with chest X-ray assessments date: 2019-03-25 journal: Radiol Med DOI: 10.1007/s11547-019-01024-w sha: doc_id: 6708 cord_uid: nionk55w BACKGROUND: Crimean–Congo hemorrhagic fever (CCHF), characterized by fever and/or hemorrhage, is a zoonotic viral disease with high mortality. Since patients have cold-like symptoms in pre-hemorrhagic phase, there may be some difficulties in differential diagnosis.


id: cord-312251-t6omrr07
author: Vancheri, Sergio Giuseppe
date: 2020-05-30
extension: .txt
mime: text/plain
words: 3509
sentence: 154
flesch: 44
cache: cache/cord-312251-t6omrr07.txt
txt: txt/cord-312251-t6omrr07.txt
title:
  Radiographic findings in 240 patients with COVID-19 pneumonia: time-dependence after the onset of symptoms

summary:
  The most frequent lesions in COVID-19 patients were GGO (intermediate/late phase) and reticular alteration (early phase) while consolidation gradually increased over time. During the subsequent outbreak in the Western world, chest X-ray (CXR), together with arterial blood gas analysis and clinical presentation, in patients positive to RT-PCR, was recommended as a useful and easily available tool to support the initial diagnosis and for the subsequent management of COVID-19 patients [7, 8] .


id: cord-327257-doygrgrc
author: Zhu, Jocelyn
date: 2020-07-28
extension: .txt
mime: text/plain
words: 3689
sentence: 188
flesch: 48
cache: cache/cord-327257-doygrgrc.txt
txt: txt/cord-327257-doygrgrc.txt
title:
  Deep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs

summary:
  Deep-learning convolutional neural network (CNN) was used to predict lung disease severity scores. [12, 13] with an additional regression layer was utilized to predict disease severity scores of CXR on a graded scale.


id: cord-013065-oj0wsstz
author: Rodríguez-Fanjul, Javier
date: 2020-10-08
extension: .txt
mime: text/plain
words: 3742
sentence: 183
flesch: 41
cache: cache/cord-013065-oj0wsstz.txt
txt: txt/cord-013065-oj0wsstz.txt
title:
  Procalcitonin and lung ultrasound algorithm to diagnose severe pneumonia in critical paediatric patients (PROLUSP study). A randomised clinical trial

summary:
  The algorithm should improve bacterial pneumonia diagnosis and therefore the treatment of either community-acquired or nosocomial pneumonia in patients with respiratory infection suspicion. To assess whether an algorithm with LUS and procalcitonin (PCT) may be useful for diagnosing bacterial pneumonia; 2.


id: cord-238881-tupom7fb
author: Yeh, Chun-Fu
title: A Cascaded Learning Strategy for Robust COVID-19 Pneumonia Chest X-Ray Screening
date: 2020-04-24
extension: .txt
mime: text/plain
words: 3358
sentence: 145
flesch: 51
cache: cache/cord-238881-tupom7fb.txt
txt: txt/cord-238881-tupom7fb.txt
summary:
  Suggested by medical experts, because of the efficiency and availability of CXR, we propose an AI-based screening system to recognize COVID-19 pneumonia in CXR images. The frequent changes in the available training data may require re-training the AI model to improve classification performance on COVID-19 images, while it also may degrade the overall pneumonia classification in stage 2.


id: cord-336843-c0sr3six
author: Gerritsen, M. G.
date: 2017-02-24
extension: .txt
mime: text/plain
words: 4327
sentence: 190
flesch: 44
cache: cache/cord-336843-c0sr3six.txt
txt: txt/cord-336843-c0sr3six.txt
title:
  Improving early diagnosis of pulmonary infections in patients with febrile neutropenia using low-dose chest computed tomography

summary:
  Management of febrile neutropenia: ESMO Clinical Practice Guidelines A prospective survey of febrile events in hematological malignancies The utility of routine chest radiography in the initial evaluation of adult patients with febrile neutropenia patients undergoing HSCT Clinical practice guideline for the use of antimicrobial agents in neutropenic patients with cancer: 2010 update by the infectious diseases society of america. Two previous studies have compared the use of CXR with LDCT in febrile neutropenic patients.


id: cord-127759-wpqdtdjs
author: Qi, Xiao
date: 2020-11-06
extension: .txt
mime: text/plain
words: 3915
sentence: 203
flesch: 47
cache: cache/cord-127759-wpqdtdjs.txt
txt: txt/cord-127759-wpqdtdjs.txt
title:
  Chest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network

summary:
  Although numerous studies have shown the capability of CNNs in effective identification of COVID-19 from CXR images, none of these studies investigated local phase CXR image features as multi-feature input to a CNN architecture for improved diagnosis of COVID-19 disease. In this study, we design a novel multi-feature convolutional neural network (CNN) architecture for multi-class improved classification of COVID-19 from CXR images.


id: cord-303483-wendrxee
author: Rubin, Geoffrey D.
date: 2020-04-07
extension: .txt
mime: text/plain
words: 4318
sentence: 136
flesch: 28
cache: cache/cord-303483-wendrxee.txt
txt: txt/cord-303483-wendrxee.txt
title:
  The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society

summary:
  Separate ratings were obtained for COVID-19 positive patients and either COVID-19 negative patients or patients for whom COVID-19 testing is unavailable (Fig 2, Q6 & Q7) . For COVID-19 positive patients, imaging establishes baseline pulmonary status and identifies underlying cardiopulmonary abnormalities that may facilitate risk stratification for clinical worsening.


id: cord-346942-88l03lf0
author: Kerpel, Ariel
title: Diagnostic and Prognostic Value of Chest Radiographs for COVID-19 at Presentation
date: 2020-08-17
extension: .txt
mime: text/plain
words: 4484
sentence: 194
flesch: 47
cache: cache/cord-346942-88l03lf0.txt
txt: txt/cord-346942-88l03lf0.txt
summary:
  The overall RALE score failed to identify COVID-19 patients at presentation. A high RALE score predicted a poor outcome (intensive care unit hospitalization, intubation, or death) in COVID-19 patients; a score of ≥5 substantially increased the odds of having a poor outcome.


id: cord-018027-goxdiyv3
author: Heussel, Claus Peter
title: Diagnostic Radiology in Hematological Patients with Febrile Neutropenia
date: 2014-11-27
extension: .txt
mime: text/plain
words: 4911
sentence: 218
flesch: 34
cache: cache/cord-018027-goxdiyv3.txt
txt: txt/cord-018027-goxdiyv3.txt
summary:
  Clinically, lungs are affected in 30 % of febrile neutropenic patients and allogeneic hematopoietic stem cell transplant (aSCT) recipients, paranasal sinuses in 3 % of neutropenic patients, and 30 % in the aSCT setting (concomitant to pneumonia), while the gastrointestinal tract, liver, spleen, central nervous system, and kidneys are less frequently involved [ 4 ] . Imaging diagnostics Deterioration of previous acute lung injury during neutropenia recovery Conventional chest radiography in the initial assessment of adult cancer patients with fever and neutropenia High-resolution ultrafast chest CT in the clinical management of febrile bone marrow transplant patients with normal or nonspecifi c chest roentgenograms Importance of digital thoracic radiography in the diagnosis of pulmonary infi ltrates in patients with bone marrow transplantation during aplasia Thoracic disease in the immunocompromised patient Patient doses from chest radiography in Victoria Multi-slice computed tomography as a screening tool for colon cancer, lung cancer and coronary artery disease Pneumonia in febrile neutropenic patients, bone-marrow and blood stem-cell recipients: use of high-resolution CT Computed tomography assessment of ground-glass opacity: semiology and signifi cance Pulmonary manifestations in HIV patients: the role of chest fi lms, CT and HRCT New frontiers in CT imaging of airway disease New technical developments in multislice CT -part 1: approaching isotropic resolution with sub-millimeter 16-slice scanning Thorakale Computertomographie von Lungeninfi ltraten Aneurysms complicating infl ammatory diseases in immunocompromised hosts: value of contrast-enhanced CT Noninfectious lung disease in immunocompromised patients MR imaging of pneumonia in immunocompromised patients: comparison with helical CT MRI of the lung parenchyma Increasing volume and changing characteristics of invasive pulmonary aspergillosis on sequential thoracic computed tomography scans in patients with neutropenia CT fi ndings of leukemic pulmonary infi ltration with pathologic correlation Pneumonia: high-resolution CT fi ndings in 114 patients Bacterial pneumonia in immunocompromised patients Fungal pneumonia Crescent sign in invasive pulmonary aspergillosis: frequency and related CT and clinical factors Importance of open lung biopsy in the diagnosis of invasive pulmonary aspergillosis in patients with hematologic malignancies A new name (Pneumocystis jiroveci) for Pneumocystis from humans Accuracy of high-resolution CT in distinguishing between Pneumocystis carinii pneumonia and non-Pneumocystis carinii pneumonia in AIDS patients Viral and pneumocystis carinii infections of the lung in the immunocompromised host Imaging of pulmonary tuberculosis CT of tuberculosis and nontuberculous mycobacterial infections Late CD8+ lymphocytic alveolitis after allogeneic bone marrow transplantation and chronic graft-versus-host disease Organizing pneumonia: the many morphological faces Clinical radiation pneumonitis and radiographic changes after thoracic radiation therapy for lung carcinoma High-resolution CT of drug-induced lung disease Pulmonary leukemic infi ltrates: high-resolution CT fi ndings in 10 patients Delaying the empiric treatment of candida bloodstream infection until positive blood culture results are obtained: a potential risk factor for hospital mortality New observations on the signifi cance of the air crescent in invasive pulmonary aspergillosis Invasive pulmonary aspergillosis in acute leukemia: characteristic fi ndings on CT, the CT halo sign, and the role of CT in early diagnosis European Organization for Research and Treatment of Cancer/ Invasive Fungal Infections Cooperative Group; National Institute of Allergy and Infectious Diseases Mycoses Study Group (EORTC/MSG) Consensus Group.


id: cord-269014-ck27fm58
author: Vo, Luan Nguyen Quang
date: 2020-09-14
extension: .txt
mime: text/plain
words: 5041
sentence: 203
flesch: 45
cache: cache/cord-269014-ck27fm58.txt
txt: txt/cord-269014-ck27fm58.txt
title:
  Enhanced Private Sector Engagement for Tuberculosis Diagnosis and Reporting through an Intermediary Agency in Ho Chi Minh City, Viet Nam

summary:
  The level of USD 22.07 proved sufficient to elicit private TB treatment reports among some, but it is safe to say that the 14 reporting providers in our study did not constitute the entire spectrum of private TB treatment. This pilot investigated the feasibility of building a portfolio of private providers and measured the outputs of incentivizing and supporting referral and reporting of private TB treatment.


id: cord-292341-uo54ghf3
author: Cocconcelli, Elisabetta
title: Clinical Features and Chest Imaging as Predictors of Intensity of Care in Patients with COVID-19
date: 2020-09-16
extension: .txt
mime: text/plain
words: 5198
sentence: 216
flesch: 44
cache: cache/cord-292341-uo54ghf3.txt
txt: txt/cord-292341-uo54ghf3.txt
summary:
  All these findings emphasize the importance of past medical history and comorbidities in the disease course of COVID-19 patients, as they may predispose to worse outcome and higher intensity of care. Pevious reports on CXR findings in COVID-19 patients focused on the distribution and type of lung abnormalities.


id: cord-275974-uqd30v7b
author: Shorfuzzaman, Mohammad
date: 2020-10-17
extension: .txt
mime: text/plain
words: 5441
sentence: 211
flesch: 44
cache: cache/cord-275974-uqd30v7b.txt
txt: txt/cord-275974-uqd30v7b.txt
title:
  MetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients

summary:
  The shortage of COVID-19 CXR images brings substantial challenges in developing tools for effectively diagnosing COVID-19 cases using deep learning based techniques. Our model achieves 95.6% accuracy and AUC of 0.97 in diagnosing COVID-19 from CXR images even with a limited number of training samples.


id: cord-006683-7rsmbk3j
author: Coppola, M.
date: 2011-01-12
extension: .txt
mime: text/plain
words: 4840
sentence: 219
flesch: 44
cache: cache/cord-006683-7rsmbk3j.txt
txt: txt/cord-006683-7rsmbk3j.txt
title:
  Influenza A virus: radiological and clinical findings of patients hospitalised for pandemic H1N1 influenza

summary:
  caratteristiche radiologiche e cliniche di un'ampia popolazione di pazienti ospedalizzati in un centro di riferimento per le malattie infettive con diagnosi accertata, mediante tampone faringeo, di infl uenza virale H1N1. Our study describes the radiological and clinical characteristics of a large population of patients affected by H1N1 infl uenza.


id: cord-103840-2diao7zh
author: Mungai, B. N.
date: 2020-08-22
extension: .txt
mime: text/plain
words: 5915
sentence: 277
flesch: 46
cache: cache/cord-103840-2diao7zh.txt
txt: txt/cord-103840-2diao7zh.txt
title:
  It's not TB but what could it be? Abnormalities on chest X-rays taken during the Kenya National Tuberculosis Prevalence Survey

summary:
  4 Computer-Aided Detection for Tuberculosis (CAD4TB) demonstrates high sensitivity for CXR TB diagnosis but is not calibrated for detection of non-TB abnormalities. Implementation of CXR TB screening in this context requires detailed health system planning to incorporate provision of care to people with non-TB abnormalities.


id: cord-355218-eici4eit
author: Punn, Narinder Singh
date: 2020-10-17
extension: .txt
mime: text/plain
words: 5954
sentence: 250
flesch: 42
cache: cache/cord-355218-eici4eit.txt
txt: txt/cord-355218-eici4eit.txt
title:
  Automated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks

summary:
  Covid-caps: a capsule network-based framework for identification of covid-19 cases from x-ray images Eosinophilic lung diseases Covid-19: automatic detection from x-ray images utilizing transfer learning with convolutional neural networks The diagnostic evaluation of convolutional neural network (cnn) for the assessment of chest x-ray of patients infected with covid-19 Adaptive total variation denoising based on difference curvature Deep learning-based image conversion of ct reconstruction kernels improves radiomics reproducibility for pulmonary nodules or masses A novel transfer learning based approach for pneumonia detection in chest x-ray images Covid-19 image data collection Imagenet: a large-scale hierarchical image database Covid-resnet: a deep learning framework for screening of covid19 from radiographs Deep learning in medical image analysis: a third eye for doctors Low-light image enhancement of high-speed endoscopic videos using a convolutional neural network The origin, transmission and clinical therapies on coronavirus disease 2019 (covid-19) outbreak-an update on the status Finding covid-19 from chest x-rays using deep learning on a small dataset Computer Vision: A Reference Guide Deep residual learning for image recognition Densely connected convolutional networks Chexpert: a large chest radiograph dataset with uncertainty labels and expert comparison Two public chest x-ray datasets for computer-aided screening of pulmonary diseases Using deep learning to detect pneumonia caused by ncov-19 from x-ray images Survey on deep learning with class imbalance Identifying medical diagnoses and treatable diseases by image-based deep learning Detection of coronavirus (covid-19) associated pneumonia based on generative adversarial networks and a fine-tuned deep transfer learning model using chest x-ray dataset Loss functions in classification tasks Imagenet classification with deep convolutional neural networks Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks A transfer learning method with deep residual network for pediatric pneumonia diagnosis A survey of deep neural network architectures and their applications Differentiable learning-to-normalize via switchable normalization The forthcoming artificial intelligence (ai) revolution: its impact on society and firms Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks Chexnet: an in-depth review Deep learning covid-19 features on cxr using limited training data sets Image thresholding Deep anomaly detection with deviation networks Covid-19 posteroanterior chest x-ray fused (cpcxr) dataset Inception u-net architecture for semantic segmentation to identify nuclei in microscopy cell images Covid-19 epidemic analysis using machine learning and deep learning algorithms medRxiv Harmony-search and otsu based system for coronavirus disease (covid-19) detection using lung ct scan images Deep learning for chest radiograph diagnosis: a retrospective comparison of the chexnext algorithm to practicing radiologists Explaining the predictions of any classifier U-net: convolutional networks for biomedical image segmentation An overview of gradient descent optimization algorithms Classification of images of childhood pneumonia using convolutional neural networks Grad-cam: visual explanations from deep networks via gradient-based localization Detection of coronavirus disease (covid-19) based on deep features Deep learning in medical image analysis Deep inside convolutional networks: visualising image classification models and saliency maps Very deep convolutional networks for large-scale image recognition Pneumonia dataset annotation methods. COVID-19 image dataset is a public database of pneumonia cases with CXR images related to COVID-19, MERS, SARS, and ARDS collected by Cohen et al.


id: cord-294557-4h0sybiy
author: Stogiannos, N.
title: Coronavirus disease 2019 (COVID-19) in the radiology department: What radiographers need to know
date: 2020-06-04
extension: .txt
mime: text/plain
words: 6731
sentence: 252
flesch: 41
cache: cache/cord-294557-4h0sybiy.txt
txt: txt/cord-294557-4h0sybiy.txt
summary:
  A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version) Acute pulmonary embolism associated with COVID-19 pneumonia detected by pulmonary CT angiography Acute pulmonary embolism in COVID-19 patients on CT angiography and relationship with D-Dimer levels Clinical and CT features in pediatric patients with COVID-19 infection: different points of adults CT features of novel coronavirus pneumonia (COVID-19) in children Differences in clinical and imaging presentation of pediatric patients with COVID-19 in comparison to adults Clinical and CT imaging features of the COVID-19 pneumonia: focus on pregnant women and children Medical Imaging plays an important auxiliary role in the diagnosis of Covid-19 patients, mainly those most seriously affected.


id: cord-157444-huvnyali
author: Nabulsi, Zaid
date: 2020-10-22
extension: .txt
mime: text/plain
words: 6807
sentence: 269
flesch: 39
cache: cache/cord-157444-huvnyali.txt
txt: txt/cord-157444-huvnyali.txt
title:
  Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases

summary:
  However, as other acute diseases may share a similar clinical presentation, many cases negative for COVID-19 exhibited abnormal CXR findings that likely triggered the DLS ( Figure 5, Supplementary Figure 5 ). The percentage of abnormal images were 24% and 71% in DS-1 and CXR-14, respectively ( Figure 2A ).


id: cord-334495-7y1la856
author: Agricola, Eustachio
title: Heart and Lung Multimodality Imaging in COVID-19
date: 2020-06-24
extension: .txt
mime: text/plain
words: 6796
sentence: 234
flesch: 25
cache: cache/cord-334495-7y1la856.txt
txt: txt/cord-334495-7y1la856.txt
summary:
  As many as 40% hospitalized patients presenting with COVID-19 have pre-existing history of cardiovascular disease and current estimates report a proportion of myocardial injury in COVID-19 patients ranging up to 12%. The use of integrated heart and lung multimodality imaging plays a central role in different clinical settings and is essential in diagnosis, risk stratification and management of COVID-19 patients.


id: cord-347691-ia2i8svg
author: Larici, Anna Rita
title: Multimodality imaging of COVID-19 pneumonia: from diagnosis to follow-up. A comprehensive review
date: 2020-08-17
extension: .txt
mime: text/plain
words: 7459
sentence: 290
flesch: 31
cache: cache/cord-347691-ia2i8svg.txt
txt: txt/cord-347691-ia2i8svg.txt
summary:
  A study of 302 patients from Italy Association between initial chest CT or clinical features and clinical course in patients with coronavirus disease 2019 pneumonia CT quantification of pneumonia lesions in early days predicts progression to severe illness in a cohort of COVID-19 patients Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort Multicenter cohort study demonstrates more consolidation in upper lungs on initial CT increases the risk of adverse clinical outcome in COVID-19 patients Well-aerated Lung on Admitting Chest CT to Predict Adverse Outcome in COVID-19 Pneumonia COVID-19 patients and the radiology departmentadvice from the European Society of Radiology (ESR) and the European Society of Thoracic Imaging (ESTI) CT in Coronavirus Disease 2019 (COVID-19): A Systematic Review of Chest CT Findings in 4410 Adult Patients CT Imaging Features of 4121 Patients With COVID-19: A Meta-Analysis Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer Histopathologic Changes and SARS-CoV-2 Immunostaining in the Lung of a Patient With COVID-19 Pathological findings of COVID-19 associated with acute respiratory distress syndrome High expression of ACE2receptor of 2019-nCoV on the epithelial cells of oral mucosa Angiotensin-converting enzyme 2 protects from severe acute lung failure The Pathogenesis and Treatment of the 'Cytokine Storm' in COVID-19 Endothelial cell infection and endotheliitis in COVID-19 Complement associated microvascular injury and thrombosis in the pathogenesis of severe COVID-19 infection: A report of five cases Difference of coagulation features between severe pneumonia induced by SARS-CoV2 and non-SARS-CoV2 Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia High-resolution Computed Tomography Findings of Acute Respiratory Distress Syndrome, Acute Interstitial Pneumonia, and Acute Exacerbation of Idiopathic Pulmonary Fibrosis Time Course of Lung Changes at Chest CT During Recovery From 2019 Novel Coronavirus (COVID-19) Clinical implications High Incidence of Barotrauma in Patients With COVID-19 Infection on Invasive Mechanical Ventilation Acute pulmonary embolism and COVID-19 Pulmonary embolism in patients with COVID-19 pneumonia Acute pulmonary embolism associated with COVID-19 pneumonia detected by pulmonary CT angiography Pulmonary embolism in COVID-19 patients: awareness of an increased prevalence Pulmonary Vascular Manifestations of COVID-19 Radiology:


id: cord-296208-uy1r6lt2
author: Greenspan, Hayit
date: 2020-08-19
extension: .txt
mime: text/plain
words: 8010
sentence: 320
flesch: 43
cache: cache/cord-296208-uy1r6lt2.txt
txt: txt/cord-296208-uy1r6lt2.txt
title:
  Position paper on COVID-19 imaging and AI: from the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare

summary:
  The COVID-19 crisis has seen the emergence of multiple observational studies to support research into understanding disease risk, monitoring disease trajectory, and for the development of diagnostic and prognostic tools, based on a variety of data sources including clinical data, samples and imaging data. It is therefore important that, while conducting efforts to provide access to observational COVID-19 data, we already plan for using part of the data for designing challenges around relevant clinical use cases.


id: cord-167889-um3djluz
author: Chen, Jianguo
title: A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19
date: 2020-07-04
extension: .txt
mime: text/plain
words: 12258
sentence: 626
flesch: 46
cache: cache/cord-167889-um3djluz.txt
txt: txt/cord-167889-um3djluz.txt
summary:
  The radiological signs of COVID-19 CXR images include airspace opacity, GGO, and later mergers. The architecture of the COVID-19 outbreak prediction model based on AI models is shown in Fig.


id: cord-015352-2d02eq3y
title: ESPR 2017
date: 2017-04-26
extension: .txt
mime: text/plain
words: 82384
sentence: 3820
flesch: 43
cache: cache/cord-015352-2d02eq3y.txt
txt: txt/cord-015352-2d02eq3y.txt
summary:
  In 2011, the image gently campaign released a safety checklist for performing digital radiography examinations on pediatric patients which is easily applicable to every radiology service. Health care professionals have a shared responsibility for communicating risks and benefits of imaging procedures to patients, especially in the case of pediatric patients.


# ent

id: cord-018027-goxdiyv3
sid: 214
eid: 2
type: PERSON
entity:
  infektiöser komplikationen nach allogener stammzelltransplantation diagnostik und therapie von lungeninfi ltraten bei febrilen neutropenischen patienten -leitlinien


