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Deep Learning Predicts Cardiovascular Disease Risks from Lung Cancer Screening Low Dose Computed Tomography [article]

Hanqing Chao, Hongming Shan, Fatemeh Homayounieh, Ramandeep Singh, Ruhani Doda Khera, Hengtao Guo, Timothy Su, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
<span title="2020-08-16">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Given the dominance of low dose computed tomography (LDCT) for lung cancer screening, the feasibility of extracting information on CVD from the same LDCT scan would add major value to patients at no additional  ...  The high risk population of cardiovascular disease (CVD) is simultaneously at high risk of lung cancer.  ...  The authors thank the National Cancer Institute (NCI) for access to NCIs data collected by the National Lung Screening Trial.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2008.06997v1">arXiv:2008.06997v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ojelmuunbrfsjpdxuhfh2y4hq4">fatcat:ojelmuunbrfsjpdxuhfh2y4hq4</a> </span>
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Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography

Hanqing Chao, Hongming Shan, Fatemeh Homayounieh, Ramandeep Singh, Ruhani Doda Khera, Hengtao Guo, Timothy Su, Ge Wang, Mannudeep K. Kalra, Pingkun Yan
<span title="2021-05-20">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a4wan6l5o5dfzn767kyz7jqevi" style="color: black;">Nature Communications</a> </i> &nbsp;
Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients.  ...  Our deep learning CVD risk prediction model, trained with 30,286 LDCTs from the National Lung Cancer Screening Trial, achieves an area under the curve (AUC) of 0.871 on a separate test set of 2,085 subjects  ...  The authors thank the National Cancer Institute (NCI) for access to NCI's data collected by the National Lung Screening Trial.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/s41467-021-23235-4">doi:10.1038/s41467-021-23235-4</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34017001">pmid:34017001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cwi6j4vpu5fvjf3qqajxtine6u">fatcat:cwi6j4vpu5fvjf3qqajxtine6u</a> </span>
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The Future of Concurrent Automated Coronary Artery Calcium Scoring on Screening Low-Dose Computed Tomography

Jeffrey Waltz, Madison Kocher, Jacob Kahn, McKenzie Dirr, Jeremy R Burt
<span title="2020-06-12">2020</span> <i title="Cureus, Inc."> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/74mctp3frjfttdv6dx4dzh6lbm" style="color: black;">Cureus</a> </i> &nbsp;
Low-dose computed tomography (LDCT) has been extensively validated for lung cancer screening in selected patient populations.  ...  Patients that qualify for LDCT for lung cancer screening commonly share major risk factors for coronary artery disease and would frequently benefit from an additional gated cardiac CT for the assessment  ...  as low-dose computed tomography (LDCT) [7] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.7759/cureus.8574">doi:10.7759/cureus.8574</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32670710">pmid:32670710</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7358941/">pmcid:PMC7358941</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oh3jch22ivbz5g2cjv65atz4ee">fatcat:oh3jch22ivbz5g2cjv65atz4ee</a> </span>
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Deep Learning to Assess Long-term Mortality From Chest Radiographs

Michael T. Lu, Alexander Ivanov, Thomas Mayrhofer, Ahmed Hosny, Hugo J. W. L. Aerts, Udo Hoffmann
<span title="2019-07-19">2019</span> <i title="American Medical Association (AMA)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/aj4ubaiwqfeknejtsyuk2st4su" style="color: black;">JAMA Network Open</a> </i> &nbsp;
to screening chest radiography vs low-dose chest computed tomography; the trial's primary finding was that chest computed tomography reduced lung cancer mortality by 20% compared with chest radiography  ...  For persons in the high-and very high-risk categories, a reasonable first step would be to confirm guidelines-appropriate lung cancer screening with computed tomography, as well as cardiovascular and respiratory  ...  National Lung Screening Trial testing data is available from the National Cancer Institute and the ACRIN.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1001/jamanetworkopen.2019.7416">doi:10.1001/jamanetworkopen.2019.7416</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31322692">pmid:31322692</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6646994/">pmcid:PMC6646994</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pr6y6ki4zrdn5ay45rnwumedg4">fatcat:pr6y6ki4zrdn5ay45rnwumedg4</a> </span>
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Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method

Peng Huang, Cheng T Lin, Yuliang Li, Martin C Tammemagi, Malcolm V Brock, Sukhinder Atkar-Khattra, Yanxun Xu, Ping Hu, John R Mayo, Heidi Schmidt, Michel Gingras, Sergio Pasian (+8 others)
<span title="2019-10-17">2019</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tc54ndgskvaxfmi4eu6cvvip7q" style="color: black;">The Lancet Digital Health</a> </i> &nbsp;
We aimed at developing a more accurate screening protocol by estimating the 3-year lung cancer risk after two screening CTs using deep machine learning (ML) of radiologist CT reading and other universally  ...  A deep machine learning (ML) algorithm was developed from 25,097 participants who had received at least two CT screenings up to two years apart in the National Lung Screening Trial.  ...  Hopkins University Whiting School of Engineering IT group in providing support and maintenance of our webbased machine learning tool.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/s2589-7500(19)30159-1">doi:10.1016/s2589-7500(19)30159-1</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32864596">pmid:32864596</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7450858/">pmcid:PMC7450858</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5734zfn5nrfctfc6p2vdo6s3ay">fatcat:5734zfn5nrfctfc6p2vdo6s3ay</a> </span>
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Early imaging biomarkers of lung cancer, COPD and coronary artery disease in the general population: rationale and design of the ImaLife (Imaging in Lifelines) Study

Congying Xia, Mieneke Rook, Gert Jan Pelgrim, Grigory Sidorenkov, Hendrik J. Wisselink, Jurjen N. van Bolhuis, Peter M. A. van Ooijen, Jiapan Guo, Matthijs Oudkerk, Harry Groen, Maarten van den Berge, Pim van der Harst (+8 others)
<span title="2019-04-23">2019</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3lw5bqcwyrbrfcgqv6q5rpo5la" style="color: black;">European Journal of Epidemiology</a> </i> &nbsp;
State-of-the-art computed tomography (CT) allows early detection of lung cancer and simultaneous evaluation of imaging biomarkers for the early stages of COPD, based on pulmonary density and bronchial  ...  The ImaLife study will allow differentiation between normal aging of the pulmonary and cardiovascular system and early stages of the big three diseases based on low-dose CT imaging.  ...  Lung cancer screening using low-dose chest CT is now recommended to detect early cases of lung cancer [2] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10654-019-00519-0">doi:10.1007/s10654-019-00519-0</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/31016436">pmid:31016436</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ij6hqf7z5jblbifgbufy3swgvu">fatcat:ij6hqf7z5jblbifgbufy3swgvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200506020012/https://www.rug.nl/research/portal/files/81171947/Xia2019_Article_EarlyImagingBiomarkersOfLungCa.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4a/2b/4a2b6afc1a477163c7c951d18384b5148eff6599.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10654-019-00519-0"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

The radiologist's role in lung cancer screening

Annemiek Snoeckx, Caro Franck, Mario Silva, Mathias Prokop, Cornelia Schaefer-Prokop, Marie-Pierre Revel
<span title="">2021</span> <i title="AME Publishing Company"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/e4pgye6ikzcorllih5x3ewnhoq" style="color: black;">Translational Lung Cancer Research</a> </i> &nbsp;
Large randomized controlled trials have shown that lung cancer screening (LCS) with low-dose computed tomography (CT) can detect lung cancers at earlier stages and reduce lung cancer-specific mortality  ...  Lung cancer is still the deadliest cancer in men and women worldwide. This high mortality is related to diagnosis in advanced stages, when curative treatment is no longer an option.  ...  In 2011, the National Lung Screening Trial (NLST) showed that participants who received low-dose computed tomography (LDCT) scans had a 20% lower risk of dying of lung cancer compared to participants who  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21037/tlcr-20-924">doi:10.21037/tlcr-20-924</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34164283">pmid:34164283</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8182709/">pmcid:PMC8182709</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yiyjnj7rxbef3poctlikfdap7a">fatcat:yiyjnj7rxbef3poctlikfdap7a</a> </span>
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Deep Learning Based Long Term Mortality Prediction in the National Lung Screening Trial

Yaozhi Lu, Shahab Aslani, Mark Emberton, Daniel C. Alexander, Joseph Jacob.
<span title="">2022</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
In this study, the long-term mortality in the National Lung Screening Trial (NLST) was investigated using a deep learning-based method.  ...  Binary classification of the non-lung-cancer mortality (i.e. cardiovascular and respiratory mortality) was performed using neural network models centered around a 3D-ResNet.  ...  ACKNOWLEDGMENT The authors would like to thank the National Cancer Institute for access to NCI's data collected by the National Lung Screening Trial (NLST).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2022.3161954">doi:10.1109/access.2022.3161954</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gdngkkb3tbgizagl2lnp37nwai">fatcat:gdngkkb3tbgizagl2lnp37nwai</a> </span>
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Review of the future of lung cancer screening

Rowena Yip, Artit Jirapatnakul, Meng Li, David F. Yankelevitz, Claudia I. Henschke
<span title="">2021</span> <i title="AME Publishing Company"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jzzdnhj2bbax7asmsnlelukv5a" style="color: black;">Current Challenges in Thoracic Surgery</a> </i> &nbsp;
Another recent study developed a deep learning algorithm to predict the risk of lung cancer (88) .  ...  The future of AI in lung cancer screening lies in the integration of algorithms that detect and diagnose all diseases visible in a LDCT, not only lung cancer but emphysema, interstitial lung disease, cardiovascular  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21037/ccts-20-125">doi:10.21037/ccts-20-125</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uxd5tcrlcnelrbppbjas7cyhu4">fatcat:uxd5tcrlcnelrbppbjas7cyhu4</a> </span>
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Applications of artificial intelligence in the thorax: a narrative review focusing on thoracic radiology

Yisak Kim, Ji Yoon Park, Eui Jin Hwang, Sang Min Lee, Chang Min Park
<span title="">2021</span> <i title="AME Publishing Company"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zg4pruoxwzcbtkfe5chpq7zkmi" style="color: black;">Journal of Thoracic Disease</a> </i> &nbsp;
Artificial intelligence (AI); deep learning (DL); computer aided diagnosis (CAD); thoracic radiology; pulmonary medicine.  ...  We also introduce prominent examples of recent AI applications, such as tuberculosis screening in resource-constrained environments, the detection of lung cancer with screening CT, and the diagnosis of  ...  The US National Lung Screening Trial (NLST) research team found that screening for lung cancer with low-dose CT (LDCT) in high-risk populations could reduce mortality from lung cancer by 20% (82) .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21037/jtd-21-1342">doi:10.21037/jtd-21-1342</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35070379">pmid:35070379</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8743417/">pmcid:PMC8743417</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3fradsihgna35gow6fe3cehfxy">fatcat:3fradsihgna35gow6fe3cehfxy</a> </span>
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Front Matter: Volume 9414

<span title="2015-05-11">2015</span> <i title="SPIE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xfwg4fmybzazfktmdtzvhcujka" style="color: black;">Medical Imaging 2015: Computer-Aided Diagnosis</a> </i> &nbsp;
The publisher is not responsible for the validity of the information or for any outcomes resulting from reliance thereon.  ...  in lung nodule volume estimation with CT: comparisons of findings from two estimation methods in a phantom study VESSELS, HEART AND EYE I 0D Automatic machine learning based prediction of cardiovascular  ...  02 Automatic diagnosis of inflammatory muscle disease for MRI using computer-extracted features of bivariate histograms 9414 03 Segmentation of the sternum from low-dose chest CT images 9414 04 Detection  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2194210">doi:10.1117/12.2194210</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/micad/X15.html">dblp:conf/micad/X15</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wzirgkwiwbgvba6jlaucm3azzq">fatcat:wzirgkwiwbgvba6jlaucm3azzq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180720112145/https://www.spiedigitallibrary.org/conference-proceedings-of-spie/9414/941401/Front-Matter-Volume-9414/10.1117/12.2194210.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3f/14/3f1445a18f5867d9c949a024f1899308df73977c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1117/12.2194210"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Artificial intelligence in pulmonary medicine: computer vision, predictive model and COVID-19

Danai Khemasuwan, Jeffrey S. Sorensen, Henri G. Colt
<span title="2020-09-30">2020</span> <i title="European Respiratory Society (ERS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i7rifwqqxnfyphfdjsv4kpe5lm" style="color: black;">European Respiratory Review</a> </i> &nbsp;
First, we describe the concept of AI and some of the requisites of machine learning and deep learning.  ...  Next, we review some of the literature relevant to the use of computer vision in medical imaging, predictive modelling with machine learning, and the use of AI for battling the novel severe acute respiratory  ...  Lung cancer screening using low-dose computed tomography (CT) has been shown to reduce mortality by 20% in the National Cancer Institute's National Lung Screening Trial (NLST).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1183/16000617.0181-2020">doi:10.1183/16000617.0181-2020</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33004526">pmid:33004526</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/3mn3hxfq6ncizhrfczbyo3vs6u">fatcat:3mn3hxfq6ncizhrfczbyo3vs6u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201003171652/https://err.ersjournals.com/content/errev/29/157/200181.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/89/4e/894eccbdf9b4215144f61fc7b32c7434af7cf20a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1183/16000617.0181-2020"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Automatic coronary artery calcium scoring on routine chest computed tomography (CT): comparison of a deep learning algorithm and a dedicated calcium scoring CT

Cheng Xu, Heng Guo, Minfeng Xu, Miao Duan, Ming Wang, Peijun Liu, Xinyi Luo, Zhengyu Jin, Hui Liu, Yining Wang
<span title="">2021</span> <i title="AME Publishing Company"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/loautdcoere2pnt4xwr4hiv3yi" style="color: black;">Quantitative Imaging in Medicine and Surgery</a> </i> &nbsp;
For the cardiovascular risk category, the deep learning algorithm accurately classified 71% of cases in group A and 81% of cases in group B.  ...  The aim of this study was to investigate the reliability and accuracy of automatic coronary artery calcium (CAC) scoring and risk classification in non-gated, non-contrast chest computed tomography (CT  ...  The technique may be promising for clinical use, and may enable cardiovascular risk assessment to be undertaken while simultaneously screening for lung diseases on chest CT.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21037/qims-21-1017">doi:10.21037/qims-21-1017</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/35502379">pmid:35502379</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC9014138/">pmcid:PMC9014138</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iauym6henrcwfjvqqpxp3ezdmi">fatcat:iauym6henrcwfjvqqpxp3ezdmi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220310104555/https://qims.amegroups.com/article/viewFile/90774/pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e2/dc/e2dc795a1702881d21a368e095fc89b6553dc510.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21037/qims-21-1017"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9014138" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Imaging methods used in the assessment of environmental disease networks: a brief review for clinicians

Aime Cedillo-Pozos, Sergey K. Ternovoy, Ernesto Roldan-Valadez
<span title="2020-02-07">2020</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5pgrqns2fjcohbjg75bidocc3y" style="color: black;">Insights into Imaging</a> </i> &nbsp;
ultrasonography and MRS; Lungs (smoke inhalation, organophosphates poisoning) are mainly assessed with radiography; Gastrointestinal system (chronic inflammatory bowel disease), recent studies have reported  ...  Contemporary imaging methods in the last 15 years started reporting alterations in different human systems such as the central nervous system, cardiovascular system and pulmonary system among others; evidence  ...  effect, which will help us predict better when a patient is at risk of suffering from a disease these tools are named computer-aided design (CAD).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13244-019-0814-7">doi:10.1186/s13244-019-0814-7</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32034587">pmid:32034587</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7007482/">pmcid:PMC7007482</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ykhxgdv6q5ebrovndo3elzsl3e">fatcat:ykhxgdv6q5ebrovndo3elzsl3e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200503120738/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC7007482&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e1/48/e148365eca95779dad9521e0106fa46833996c46.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13244-019-0814-7"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7007482" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Artificial intelligence in cancer imaging: Clinical challenges and applications

Wenya Linda Bi, Ahmed Hosny, Matthew B. Schabath, Maryellen L. Giger, Nicolai J. Birkbak, Alireza Mehrtash, Tavis Allison, Omar Arnaout, Christopher Abbosh, Ian F. Dunn, Raymond H. Mak, Rulla M. Tamimi (+7 others)
<span title="2019-02-05">2019</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/75x3imkf4fb3bh5nbuv4djxluq" style="color: black;">Ca</a> </i> &nbsp;
, extrapolation of the tumor genotype and biological course from its radiographic phenotype, prediction of clinical outcome, and assessment of the impact of disease and treatment on adjacent organs.  ...  Radiographic assessment of disease most commonly relies upon visual evaluations, the interpretations of which may be augmented by advanced computational analyses.  ...  The National Lung Screening Trial (NLST) demonstrated that screening with low-dose CT (LDCT) was associated with a significant 20% reduction in overall mortality among high-risk current and former smokers  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3322/caac.21552">doi:10.3322/caac.21552</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/30720861">pmid:30720861</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC6403009/">pmcid:PMC6403009</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/czsiirkbm5f7fh2ueesgnqtlhi">fatcat:czsiirkbm5f7fh2ueesgnqtlhi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201103070429/https://discovery.ucl.ac.uk/id/eprint/10091530/1/caac.21552.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/33/35/3335a944409a9099c0d04cd053fa272f71692935.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3322/caac.21552"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6403009" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>
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