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Tytuł :
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning.
Autorzy :
Alshazly H; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany.; Mathematics Department, Faculty of Science, South Valley University, Qena 83523, Egypt.
Linse C; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany.
Barth E; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany.
Martinetz T; Institute for Neuro- and Bioinformatics, University of Lübeck, 23562 Lübeck, Germany.
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Źródło :
Sensors (Basel, Switzerland) [Sensors (Basel)] 2021 Jan 11; Vol. 21 (2). Date of Electronic Publication: 2021 Jan 11.
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Tomography, X-Ray Computed*
COVID-19/*diagnosis
Thorax/*diagnostic imaging
Algorithms ; COVID-19/diagnostic imaging ; COVID-19/virology ; Databases, Factual ; Humans ; Neural Networks, Computer ; Radiographic Image Interpretation, Computer-Assisted ; SARS-CoV-2/pathogenicity ; Thorax/pathology ; Thorax/virology
Czasopismo naukowe
Tytuł :
Determination of disease severity in COVID-19 patients using deep learning in chest X-ray images.
Autorzy :
Blain M; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA.
Kassin MT; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA.
Varble N; Philips Research North America, Cambridge, Massachusetts, USA.
Wang X; NVIDIA Corporation, Bethesda, Maryland, USA.
Xu Z; NVIDIA Corporation, Bethesda, Maryland, USA.
Xu D; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA.
Carrafiello G; Department of Radiology,Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, University of Milan, Italy.
Vespro V; Department of Radiology,Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, University of Milan, Italy.
Stellato E; Department of Radiology,Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, University of Milan, Italy.
Ierardi AM; Department of Radiology,Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, University of Milan, Italy.
Meglio LD; Department of Radiology,Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, University of Milan, Italy.
D Suh R; Department of Radiology, University of California Los Angeles, Los Angeles, California, USA.
A Walker S; National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Xu S; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA.
H Sanford T; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA;State University of New York Upstate Medical University, Syracuse, Newyork, USA.
B Turkbey E; Molecular Imaging Program, National Institutes of Health, Bethesda, Maryland, USA;Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Mayland, USA.
Harmon S; National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA;Clinical Research Directorate, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA.
Turkbey B; Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Mayland, USA.
J Wood B; Center for Interventional Oncology, National Institutes of Health Clinical Center and National Cancer Institute, Bethesda, Maryland, USA;Department of Radiology, University of California Los Angeles, Los Angeles, California, USA;Department of Radiology and Imaging Sciences, National Institutes of Health, Bethesda, Mayland, USA.
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Źródło :
Diagnostic and interventional radiology (Ankara, Turkey) [Diagn Interv Radiol] 2021 Jan; Vol. 27 (1), pp. 20-27.
Typ publikacji :
Journal Article
MeSH Terms :
COVID-19/*diagnosis
Deep Learning/*statistics & numerical data
Radiography, Thoracic/*methods
SARS-CoV-2/*genetics
Thorax/*diagnostic imaging
Adult ; Age Factors ; Aged ; COVID-19/epidemiology ; COVID-19/therapy ; COVID-19/virology ; Comorbidity ; Feasibility Studies ; Female ; Humans ; Italy/epidemiology ; Male ; Middle Aged ; Radiography, Thoracic/classification ; Radiologists ; Retrospective Studies ; Severity of Illness Index ; Thorax/pathology
Czasopismo naukowe
Tytuł :
Calcification of the thoracic aorta on low-dose chest CT predicts severe COVID-19.
Autorzy :
Fervers P; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Kottlors J; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Zopfs D; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Bremm J; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Maintz D; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Safarov O; Department of Radiology, Helios Dr. Horst Schmidt Kliniken Wiesbaden, Wiesbaden, Germany.
Tritt S; Department of Radiology, Helios Dr. Horst Schmidt Kliniken Wiesbaden, Wiesbaden, Germany.
Abdullayev N; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
Persigehl T; Department of Diagnostic and Interventional Radiology, Faculty of Medicine and University Hospital Cologne, University Cologne, Cologne, Germany.
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Źródło :
PloS one [PLoS One] 2020 Dec 23; Vol. 15 (12), pp. e0244267. Date of Electronic Publication: 2020 Dec 23 (Print Publication: 2020).
Typ publikacji :
Journal Article
MeSH Terms :
Radiation Dosage*
Tomography, X-Ray Computed*
COVID-19/*diagnostic imaging
Thorax/*diagnostic imaging
Adult ; Aorta, Thoracic/diagnostic imaging ; Aorta, Thoracic/pathology ; Aorta, Thoracic/radiation effects ; Aorta, Thoracic/virology ; COVID-19/diagnosis ; COVID-19/therapy ; COVID-19/virology ; Critical Care ; Female ; Hospitalization ; Humans ; Intubation, Intratracheal/methods ; Lung/diagnostic imaging ; Lung/pathology ; Lung/radiation effects ; Lung/virology ; Male ; Middle Aged ; Patient Admission ; SARS-CoV-2/pathogenicity ; SARS-CoV-2/radiation effects ; Thorax/pathology ; Thorax/radiation effects ; Thorax/virology
Czasopismo naukowe
Tytuł :
Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection.
Autorzy :
Albadr MAA; CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Tiun S; CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Ayob M; CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Al-Dhief FT; Department of Communication Engineering, School of Electrical Engineering, Universiti Teknologi Malaysia, UTM Johor Bahru, Johor, Malaysia.
Omar K; CAIT, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Hamzah FA; Department of Emergency Medicine, Hospital Canselor Tuanku Muhriz, Universiti Kebangsaan Malaysia Medical Centre, Bandar Tun Razak, Cheras, Kuala Lumpur, Malaysia.
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Źródło :
PloS one [PLoS One] 2020 Dec 15; Vol. 15 (12), pp. e0242899. Date of Electronic Publication: 2020 Dec 15 (Print Publication: 2020).
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Machine Learning*
COVID-19/*diagnosis
SARS-CoV-2/*isolation & purification
Thorax/*diagnostic imaging
Algorithms ; COVID-19/diagnostic imaging ; COVID-19/physiopathology ; Humans ; Lung/diagnostic imaging ; Lung/physiopathology ; Lung/virology ; Neural Networks, Computer ; SARS-CoV-2/pathogenicity ; Support Vector Machine ; Thorax/physiopathology ; Thorax/virology ; Tomography, X-Ray Computed
Czasopismo naukowe
Tytuł :
Computed tomography characterization and outcome evaluation of COVID-19 pneumonia complicated by venous thromboembolism.
Autorzy :
Meiler S; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.
Hamer OW; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.; Department of Radiology, Hospital Donaustauf, Donaustauf, Germany.
Schaible J; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.
Zeman F; Center for Clinical Studies, Regensburg University Medical Center, Regensburg, Germany.
Zorger N; Department of Radiology, Hospital Barmherzige Brueder, Regensburg, Germany.
Kleine H; Department of Pneumology, Hospital Barmherzige Brueder, Regensburg, Germany.
Rennert J; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.
Stroszczynski C; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.
Poschenrieder F; Department of Radiology, Regensburg University Medical Center, Regensburg, Germany.
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Źródło :
PloS one [PLoS One] 2020 Nov 19; Vol. 15 (11), pp. e0242475. Date of Electronic Publication: 2020 Nov 19 (Print Publication: 2020).
Typ publikacji :
Journal Article
MeSH Terms :
Thorax*/pathology
Thorax*/ultrastructure
Coronavirus Infections/*complications
Pneumonia, Viral/*complications
Pulmonary Embolism/*diagnostic imaging
Venous Thromboembolism/*diagnostic imaging
Adult ; Aged ; Aged, 80 and over ; Betacoronavirus ; COVID-19 ; Female ; Humans ; Male ; Middle Aged ; Outcome Assessment, Health Care ; Pandemics ; Pulmonary Embolism/etiology ; Retrospective Studies ; SARS-CoV-2 ; Venous Thromboembolism/etiology
Czasopismo naukowe
Tytuł :
Chest Computed Tomography Scoring in Patients With Novel Coronavirus-infected Pneumonia: Correlation With Clinical and Laboratory Features and Disease Outcome.
Autorzy :
Pugliese L; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Sbordone FP; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Grimaldi F; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Ricci F; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
DI Tosto F; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Spiritigliozzi L; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
DI Donna C; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Presicce M; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
DE Stasio V; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Benelli L; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
D'Errico F; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Pasqualetto M; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Legramante JM; Department of System Medicine, Tor Vergata University, and Emergency Department, Rome, Italy.
Materazzo M; Breast Unit, Department of Surgical Science, Policlinico Tor Vergata University, Rome, Italy .
Pellicciaro M; Breast Unit, Department of Surgical Science, Policlinico Tor Vergata University, Rome, Italy.
Buonomo OC; Breast Unit, Department of Surgical Science, Policlinico Tor Vergata University, Rome, Italy.
Vanni G; Breast Unit, Department of Surgical Science, Policlinico Tor Vergata University, Rome, Italy.
Rizza S; Department of System Medicine, Tor Vergata University, and Department of Medical Sciences, Policlinico Tor Vergata, Rome, Italy.
Bellia A; Department of System Medicine, Tor Vergata University, and Department of Medical Sciences, Policlinico Tor Vergata, Rome, Italy.
Floris R; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Garaci F; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
Chiocchi M; Department of Biomedicine and Prevention, Division of Diagnostic Imaging, Tor Vergata University, and Unit of Diagnostic Imaging, Policlinico Tor Vergata, Rome, Italy.
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Źródło :
In vivo (Athens, Greece) [In Vivo] 2020 Nov-Dec; Vol. 34 (6), pp. 3735-3746.
Typ publikacji :
Journal Article
MeSH Terms :
Coronavirus Infections/*diagnostic imaging
Pneumonia/*diagnostic imaging
Pneumonia, Viral/*diagnostic imaging
Thorax/*diagnostic imaging
Aged ; Aged, 80 and over ; Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/mortality ; Coronavirus Infections/physiopathology ; Coronavirus Infections/therapy ; Coronavirus Infections/virology ; Female ; Hospitalization ; Humans ; Intensive Care Units ; Male ; Middle Aged ; Pandemics ; Pneumonia/mortality ; Pneumonia/physiopathology ; Pneumonia/virology ; Pneumonia, Viral/physiopathology ; Pneumonia, Viral/therapy ; Pneumonia, Viral/virology ; SARS-CoV-2 ; Thorax/physiopathology ; Thorax/virology ; Tomography, X-Ray Computed
Czasopismo naukowe
Tytuł :
Assessing thoraco-pelvic covariation in Homo sapiens and Pan troglodytes: A 3D geometric morphometric approach.
Autorzy :
Torres-Tamayo N; Departamento de Paleobiología, Museo Nacional de Ciencias Naturales (CSIC), Madrid, Spain.; GIAVAL Research Group, Department of Anatomy and Human Embryology, University of Valencia, Valencia, Spain.
Martelli S; UCL Centre for Integrative Anatomy (CIA), Department of Cell and Developmental Biology, Faculty of Life Sciences, London, UK.
Schlager S; Biological Anthropology, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
García-Martínez D; Departamento de Paleobiología, Museo Nacional de Ciencias Naturales (CSIC), Madrid, Spain.; Centro Nacional de Investigación sobre la Evolución Humana (CENIEH), Burgos, Spain.
Sanchis-Gimeno JA; GIAVAL Research Group, Department of Anatomy and Human Embryology, University of Valencia, Valencia, Spain.
Mata-Escolano F; ASCIRES ERESA Campanar Group, CT and MRI Unit, Valencia, Spain.
Nalla S; GIAVAL Research Group, Department of Anatomy and Human Embryology, University of Valencia, Valencia, Spain.; Department of Human Anatomy and Physiology, Faculty of Health Sciences, University of Johannesburg, Johannesburg, South Africa.
Ogihara N; Department of Biological Science, Graduate School of Science, The University of Tokyo, Tokyo, Japan.
Oishi M; Laboratory of Anatomy 1, School of Veterinary Medicine, Azabu University, Sagamihara, Japan.
Bastir M; Departamento de Paleobiología, Museo Nacional de Ciencias Naturales (CSIC), Madrid, Spain.
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Źródło :
American journal of physical anthropology [Am J Phys Anthropol] 2020 Nov; Vol. 173 (3), pp. 514-534. Date of Electronic Publication: 2020 Aug 30.
Typ publikacji :
Journal Article; Research Support, Non-U.S. Gov't
MeSH Terms :
Imaging, Three-Dimensional/*methods
Pan troglodytes/*anatomy & histology
Pelvis/*anatomy & histology
Thorax/*anatomy & histology
Adult ; Anatomy, Comparative ; Animals ; Anthropology, Physical ; Female ; Humans ; Male ; Pelvis/diagnostic imaging ; Sex Characteristics ; Thorax/diagnostic imaging ; Tomography, X-Ray Computed ; Young Adult
Czasopismo naukowe
Tytuł :
Regarding 'Modifications of chest radiography exposure parameters using a neonatal chest phantom' by Schäfer et al.
Autorzy :
Schneider KO; Department of Pediatric Radiology, Dr. von Hauner's Children Hospital, University of Munich LMU, Lindwurmstr. 4, 80337, Munich, Germany. .
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Źródło :
Pediatric radiology [Pediatr Radiol] 2020 Nov; Vol. 50 (12), pp. 1791. Date of Electronic Publication: 2020 Jul 24.
Typ publikacji :
Letter; Comment
MeSH Terms :
Radiography, Thoracic*
Thorax*
Humans ; Infant, Newborn ; Phantoms, Imaging ; Radiography
Opinia redakcyjna
Tytuł :
A Fine Line.
Autorzy :
Wald EL; Divisions of Critical Care and Cardiology, Ann & Robert H. Lurie Children's Hospital of Chicago and Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois.
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Źródło :
JAMA [JAMA] 2020 Oct 20; Vol. 324 (15), pp. 1501.
Typ publikacji :
Journal Article; Personal Narrative
MeSH Terms :
Foreign Bodies*/diagnostic imaging
Thorax*/diagnostic imaging
Thoracic Injuries/*pathology
Child, Preschool ; Humans ; Male ; Thoracic Injuries/diagnostic imaging ; Tomography, X-Ray Computed
Czasopismo naukowe
Tytuł :
The Effect of Chest Compression Location and Occlusion of the Aorta in a Traumatic Arrest Model.
Autorzy :
Anderson KL; Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, California. Electronic address: .
Morgan JD; San Antonio Military Medical Center, Fort Sam Houston, Texas.
Castaneda MG; CREST Research Program, Wilford Hall Ambulatory Surgical Center, Lackland AFB, Bexar County, Texas.
Boudreau SM; CREST Research Program, Wilford Hall Ambulatory Surgical Center, Lackland AFB, Bexar County, Texas.
Araña AA; United States Army Institute of Surgical Research, Fort Sam Houston, Texas.
Kohn MA; Department of Emergency Medicine, Stanford University School of Medicine, Palo Alto, California.
Bebarta VS; Department of Emergency Medicine, University of Colorado School of Medicine, Aurora, Colorado.
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Źródło :
The Journal of surgical research [J Surg Res] 2020 Oct; Vol. 254, pp. 64-74. Date of Electronic Publication: 2020 May 15.
Typ publikacji :
Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
MeSH Terms :
Aorta*
Pressure*
Thorax*
Balloon Occlusion/*methods
Heart Arrest/*etiology
Wounds and Injuries/*complications
Animals ; Cardiopulmonary Resuscitation/methods ; Disease Models, Animal ; Female ; Heart Arrest/therapy ; Heart Ventricles ; Hemodynamics ; Hemorrhage ; Prospective Studies ; Resuscitation/methods ; Sus scrofa
Czasopismo naukowe
Tytuł :
Clinical characteristics and longitudinal chest CT features of healthcare workers hospitalized with coronavirus disease 2019 (COVID-19).
Autorzy :
Liu H; Department of Radiology, The Third Xiangya Hospital, Central South University, Changsha 410013, Hunan Province, China.
Luo S; Department of Radiology, Wuhan Third Hospital (Tongren Hospital of Wuhan University); Wuhan 430060, Hubei Province, China.
Li H; Department of Radiology, Hunan Provincial People's Hospital (The first affiliate hospital of Hunan normal university), Changsha 410000, Hunan Province, China.
Zhang Y; Department of Radiology, Xiangya Hospital, Central South University, Changsha 410008, Hunan Province, China.
Huang C; Department of Chinese Medicine, First Clinical College of China Three Gorges University; Yichang 443000, Hubei Province, China.
Li X; Department of Radiology, Wuhan Third Hospital (Tongren Hospital of Wuhan University); Wuhan 430060, Hubei Province, China.
Tan Y; Department of Radiology, Wuhan Third Hospital (Tongren Hospital of Wuhan University); Wuhan 430060, Hubei Province, China.
Chen M; Department of Ultrasonography, Xiangya Hospital, Central South University, Changsha 410008, Hunan Province, China.
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Źródło :
International journal of medical sciences [Int J Med Sci] 2020 Sep 21; Vol. 17 (17), pp. 2644-2652. Date of Electronic Publication: 2020 Sep 21 (Print Publication: 2020).
Typ publikacji :
Journal Article
MeSH Terms :
Coronavirus Infections/*diagnostic imaging
Lung/*physiopathology
Pneumonia/*diagnostic imaging
Pneumonia, Viral/*diagnostic imaging
Thorax/*diagnostic imaging
Adult ; Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/physiopathology ; Coronavirus Infections/virology ; Disease Progression ; Female ; Health Personnel ; Humans ; Lung/diagnostic imaging ; Male ; Middle Aged ; Pandemics ; Pneumonia/physiopathology ; Pneumonia/virology ; Pneumonia, Viral/physiopathology ; Pneumonia, Viral/virology ; Retrospective Studies ; SARS-CoV-2 ; Thorax/physiopathology ; Thorax/virology ; Tomography, X-Ray Computed ; Young Adult
Czasopismo naukowe
Tytuł :
Artificial intelligence-enabled rapid diagnosis of patients with COVID-19.
Autorzy :
Mei X; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lee HC; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Diao KY; Department of Radiology, West China Hospital, Sichuan University, Chengdu, China.
Huang M; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lin B; Department of Radiology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Liu C; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Xie Z; Department of Radiology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, China.
Ma Y; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Robson PM; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Chung M; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Bernheim A; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Mani V; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Calcagno C; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Li K; Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yet-sen University, Zhuhai, China.
Li S; Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yet-sen University, Zhuhai, China.
Shan H; Guangdong Provincial Key Laboratory of Biomedical Imaging, The Fifth Affiliated Hospital of Sun Yet-sen University, Zhuhai, China.
Lv J; Department of Radiology, Nanxishan Hospital, Guilin, China.
Zhao T; Department of Radiology, The Second People's Hospital, Fuyang, China.
Xia J; Department of Radiology, Bozhou Bone Trauma Hospital Image Center, Bozhou, China.
Long Q; Department of Radiology, Remin Hospital of Wuhan University, Wuhan, China.
Steinberger S; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Jacobi A; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Deyer T; East River Medical Imaging, New York, NY, USA.; Department of Radiology, Weill Cornell Medicine, New York, NY, USA.
Luksza M; Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Liu F; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
Little BP; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA. .
Fayad ZA; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .
Yang Y; BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .; Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .
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Źródło :
Nature medicine [Nat Med] 2020 Aug; Vol. 26 (8), pp. 1224-1228. Date of Electronic Publication: 2020 May 19.
Typ publikacji :
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't
MeSH Terms :
Tomography, X-Ray Computed*
Betacoronavirus/*isolation & purification
Coronavirus Infections/*diagnosis
Pneumonia, Viral/*diagnosis
Thorax/*diagnostic imaging
Adult ; Artificial Intelligence ; Betacoronavirus/genetics ; Betacoronavirus/pathogenicity ; COVID-19 ; Coronavirus Infections/diagnostic imaging ; Coronavirus Infections/genetics ; Coronavirus Infections/virology ; Female ; Humans ; Male ; Middle Aged ; Pandemics ; Pneumonia, Viral/diagnostic imaging ; Pneumonia, Viral/genetics ; Pneumonia, Viral/virology ; Real-Time Polymerase Chain Reaction ; SARS-CoV-2 ; Thorax/pathology ; Thorax/virology
Czasopismo naukowe
Tytuł :
Comparison of T1-S1 Spine Height of Postoperative Rib-based Implant Patients With Age-matched Peers.
Autorzy :
Johnson MA; Divison of Orthopaedic Surgery.
Cahill PJ; Divison of Orthopaedic Surgery.
Qiu C; Divison of Orthopaedic Surgery.
Lott C; Divison of Orthopaedic Surgery.
Mayer OH; Division of Pulmonology, The Children's Hospital of Philadelphia, Philadelphia, PA.
Flynn JM; Divison of Orthopaedic Surgery.
Anari JB; Divison of Orthopaedic Surgery.
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Źródło :
Journal of pediatric orthopedics [J Pediatr Orthop] 2020 Aug; Vol. 40 (7), pp. 344-350.
Typ publikacji :
Journal Article
MeSH Terms :
Lung*/growth & development
Lung*/pathology
Orthopedic Procedures*/instrumentation
Orthopedic Procedures*/methods
Scoliosis*/complications
Scoliosis*/diagnosis
Scoliosis*/surgery
Spine*/diagnostic imaging
Spine*/growth & development
Thorax*/diagnostic imaging
Thorax*/growth & development
Ribs/*surgery
Child ; Child Development ; Female ; Humans ; Male ; Prostheses and Implants ; Radiography/methods ; Respiratory Insufficiency/etiology ; Respiratory Insufficiency/prevention & control ; Retrospective Studies
Czasopismo naukowe
Tytuł :
The Relationship Between 3-dimensional Spinal Alignment, Thoracic Volume, and Pulmonary Function in Surgical Correction of Adolescent Idiopathic Scoliosis: A 5-year Follow-up Study.
Autorzy :
Buckland AJ; Department of Orthopaedic Surgery, NYU Langone Orthopedic Hospital, Manhattan, NY.
Woo D; Department of Orthopaedic Surgery, NYU Langone Orthopedic Hospital, Manhattan, NY.
Vasquez-Montes D; Department of Orthopaedic Surgery, NYU Langone Orthopedic Hospital, Manhattan, NY.
Marks M; Setting Scoliosis Straight Foundation, San Diego, CA.
Jain A; Department of Orthopaedic Surgery, Johns Hopkins Medicine, Baltimore, MD.
Samdani A; Department of Neurosurgery, Shriners Hospital for Children, Philadelphia, PA.
Betz RR; Department of Orthopaedic Surgery, Shriners Hospital for Children, Philadelphia, PA.
Errico TJ; Department of Orthopaedic Surgery, NYU Langone Orthopedic Hospital, Manhattan, NY.
Lonner B; Department of Orthopaedic Surgery, Mount Sinai Medical Center, New York, NY.
Newton PO; Department of Orthopaedic Surgery, Rady Children's Hospital, San Diego, CA.
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Źródło :
Spine [Spine (Phila Pa 1976)] 2020 Jul 15; Vol. 45 (14), pp. 983-992.
Typ publikacji :
Journal Article
MeSH Terms :
Scoliosis*/physiopathology
Scoliosis*/surgery
Thoracic Vertebrae*/diagnostic imaging
Thoracic Vertebrae*/physiopathology
Thoracic Vertebrae*/surgery
Thorax*/diagnostic imaging
Thorax*/physiopathology
Lung/*physiology
Adolescent ; Child ; Female ; Follow-Up Studies ; Humans ; Male ; Respiratory Function Tests ; Retrospective Studies ; Treatment Outcome
Czasopismo naukowe
Tytuł :
Computerized Chest Imaging in the Diagnosis and Assessment of the Patient with Chronic Obstructive Pulmonary Disease.
Autorzy :
Pistenmaa CL; Division of Pulmonary and Critical Care, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA. Electronic address: .
Washko GR; Division of Pulmonary and Critical Care, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA.
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Źródło :
Clinics in chest medicine [Clin Chest Med] 2020 Sep; Vol. 41 (3), pp. 375-381.
Typ publikacji :
Journal Article; Research Support, N.I.H., Extramural; Review
MeSH Terms :
Lung/*diagnostic imaging
Pulmonary Disease, Chronic Obstructive/*diagnostic imaging
Thorax/*diagnostic imaging
Tomography, X-Ray Computed/*methods
Humans ; Lung/physiopathology ; Thorax/physiopathology
Czasopismo naukowe
Tytuł :
Elective localization at the upper left chest of Dermatofibrosarcoma Protuberans.
Autorzy :
Schonauer F; Unit of Plastic and Reconstructive Surgery, Federico II University of Naples, Italy. Electronic address: .
Giordano L; Unit of Plastic and Reconstructive Surgery, Federico II University of Naples, Italy.
D'Andrea F; Unit of Plastic and Reconstructive Surgery, Federico II University of Naples, Italy.
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Źródło :
Journal of plastic, reconstructive & aesthetic surgery : JPRAS [J Plast Reconstr Aesthet Surg] 2020 Sep; Vol. 73 (9), pp. e4-e5. Date of Electronic Publication: 2020 Jun 13.
Typ publikacji :
Letter
MeSH Terms :
Thorax*
Dermatofibrosarcoma/*pathology
Skin Neoplasms/*pathology
Adolescent ; Adult ; Female ; Humans ; Male ; Middle Aged ; Young Adult
Opinia redakcyjna
Tytuł :
A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.
Autorzy :
Zou XL; Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
Ren Y; Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
Feng DY; Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
He XQ; Department of Medical Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Guo YF; Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yang HL; Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
Li X; Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Yuedong Hospital, Meizhou, China.
Fang J; Department of Pumonary Diseases, Dongguan Tangxia Hospital, Dongguan, China.
Li Q; Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
Ye JJ; Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
Han LQ; Center for Artificial Intelligence in Medicine, Research Institute of Tsinghua, Pearl River Delta, Guangzhou, China.
Zhang TT; Department of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Institute of Respiratory Diseases of Sun Yat-sen University, Guangzhou, China.
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Źródło :
PloS one [PLoS One] 2020 Jul 24; Vol. 15 (7), pp. e0236378. Date of Electronic Publication: 2020 Jul 24 (Print Publication: 2020).
Typ publikacji :
Journal Article
MeSH Terms :
Deep Learning*
Hypertension, Pulmonary/*diagnostic imaging
Mass Chest X-Ray/*methods
Mass Screening/*methods
Radiographic Image Interpretation, Computer-Assisted/*methods
Thorax/*diagnostic imaging
Adult ; Aged ; Aged, 80 and over ; China ; Female ; Humans ; Hypertension, Pulmonary/epidemiology ; Male ; Middle Aged ; Retrospective Studies ; Thorax/pathology
Czasopismo naukowe
Tytuł :
An alternative way to measure respiration induced changes of circumferences: a pilot study.
Autorzy :
Laufer B
Krueger-Ziolek S
Docherty PD
Hoeflinger F
Reindl L
Moeller K
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Źródło :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2020 Jul; Vol. 2020, pp. 4632-4635.
Typ publikacji :
Journal Article
MeSH Terms :
Respiration*
Thorax*
Feasibility Studies ; Humans ; Pilot Projects ; Tidal Volume
Czasopismo naukowe
Tytuł :
Lung Region Segmentation in Chest X-Ray Images using Deep Convolutional Neural Networks.
Autorzy :
Portela RDS
Pereira JRG
Costa MGF
Filho CFFC
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Źródło :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2020 Jul; Vol. 2020, pp. 1246-1249.
Typ publikacji :
Journal Article
MeSH Terms :
Neural Networks, Computer*
Thorax*
Diagnosis, Computer-Assisted ; Lung/diagnostic imaging ; X-Rays
Czasopismo naukowe
Tytuł :
Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.
Autorzy :
Yahyatabar M
Jouvet P
Cheriet F
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Źródło :
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2020 Jul; Vol. 2020, pp. 1242-1245.
Typ publikacji :
Journal Article
MeSH Terms :
Neural Networks, Computer*
Thorax*
Diagnosis, Computer-Assisted ; Lung/diagnostic imaging ; X-Rays
Czasopismo naukowe

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