The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Chest CT for Typical Coronavirus Disease 2019 (COVID-19) Pneumonia: Relationship to Negative RT-PCR Testing
Open accessAbstract
Some patients with positive chest CT findings may present with negative results of real-time reverse-transcription polymerase chain reaction (RT-PCR) tests for coronavirus disease 2019 (COVID-19). In this study, the authors present chest CT findings from five patients with COVID-19 infection who had initial negative RT-PCR results. All five patients had typical imaging findings, including ground-glass opacity (five patients) and/or mixed ground-glass opacity and mixed consolidation (two patients). After isolation for presumed COVID-19 pneumonia, all patients were eventually confirmed to have COVID-19 infection by means of repeated swab tests. A combination of repeated swab tests and CT scanning may be helpful for individuals with a high clinical suspicion of COVID-19 infection but negative findings at RT-PCR screening.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“There are currently a number of different ways to detect COVID-19, whereas computed tomography and X-rays remain the major surgical techniques [80–82].”
From A comprehensive survey on federated learning techniques for healthcare informatics (2023) · cites this paper as [81]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A novel coronavirus from patients with pneumonia in China, 2019
Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001017 · Cited by 28,244
CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV)
Chung, M., Bernheim, A., Mei, X., Zhang, N., Huang, M., Zeng, X., Cui, J., Xu, W., Yang, Y., Fayad, Z. A., et al. (2020) · Radiology · doi:10.1148/radiol.2020200230 · Cited by 2,751
Emerging 2019 Novel Coronavirus (2019-nCoV) Pneumonia
Song, F., Shi, N., Shan, F., Zhang, Z., Shen, J., Lu, H., Ling, Y., Jiang, Y., & Shi, Y. (2020) · Radiology · doi:10.1148/radiol.2020200274 · Cited by 1,217
Kanne, J. P. (2020) · Radiology · doi:10.1148/radiol.2020200241 · Cited by 668
Severe Acute Respiratory Syndrome: Temporal Lung Changes at Thin-Section CT in 30 Patients
OOI, G. C., Khong, P. L., Müller, N. L., Yiu, W. C., Zhou, L. J., Ho, J., LAM, B. K., Nicolaou, S., & TSANG, K. W. T. (2004) · Radiology · doi:10.1148/radiol.2303030853 · Cited by 329
Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Infection: Chest CT Findings
Ajlan, A. M., Ahyad, R. A., Jamjoom, L. G., Alharthy, A., & Madani, T. A. (2014) · American Journal of Roentgenology · doi:10.2214/ajr.14.13021 · Cited by 286
Flagged first, then by citations
Cited by
Sorted by citations
Items 501–600 of 1,001
Moezzi, M., Shirbandi, K., Shahvandi, H. K., Arjmand, B., & Rahim, F. (2021) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2021.100591 · Cited by 38
A multi-scale gated multi-head attention depthwise separable CNN model for recognizing COVID-19
Hong, G., Chen, X., Chen, J., Zhang, M., Ren, Y., & Zhang, X. (2021) · Scientific Reports · doi:10.1038/s41598-021-97428-8 · Cited by 35
Wang, F., Ao, G., Wang, Y., Liu, F., Bao, M., Gao, M., Zhou, S., & Qi, X. (2021) · Renal Failure · doi:10.1080/0886022x.2021.1986408 · Cited by 34
Self-citationSerial CT features in discharged COVID-19 patients with positive RT-PCR re-test
Dou, P., Zhang, S., Wang, C., Cai, L., Liu, Z., Xu, Q., Li, X., Meng, Y., Rong, Y., Li, S., et al. (2020) · European Journal of Radiology · doi:10.1016/j.ejrad.2020.109010 · Cited by 33
“Some patients manifested typical chest CT imaging of COVID-19, without positive nucleic acid results [4] .”
Ct Findings of Covid-19 Pneumonia in Icu-Patients
Cau, R., Falaschi, Z., Paschè, A., Danna, P. S. C., Arioli, R., Arru, C. D., Zagaria, D., Tricca, S., Suri, J. S., Kalra, M. K., et al. (2021) · Journal of Public Health Research · doi:10.4081/jphr.2021.2270 · Cited by 33
Unknown SARS-CoV-2 pneumonia detected by PET/CT in patients with cancer
Scarlattei, M., Baldari, G., Silva, M., Bola, S., Sammartano, A., Migliari, S., Graziani, T., Cidda, C., Sverzellati, N., & Ruffini, L. (2020) · Tumori Journal · doi:10.1177/0300891620935983 · Cited by 33
The role of Chinese medicine in COVID-19 pneumonia: A systematic review and meta-analysis
Sun, C., Sun, Y.-L., & Li, X. (2020) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2020.06.069 · Cited by 32
“However, some studies have shown that some patients with initially negative real-time RT-PCR screening results who had typical CT findings of COVID-19 pneumonia had their RT-PCR results became positive after a few days [25].”
Capacity Evaluation of Diagnostic Tests For COVID-19 Using Multicriteria Decision-Making Techniques
Sayan, M., Yıldırım, F. S., Şanlıdağ, T., Ozsahin, D. U., Ozsahin, D. U., & Özşahin, İ. (2020) · Computational and Mathematical Methods in Medicine · doi:10.1155/2020/1560250 · Cited by 33
“Chest CT scan abnormalities have also been identified in patients prior to the development of symptoms and even prior to the detection of viral RNA from upper respiratory specimens [20, 21].”
BackgroundMamishi, S., Heydari, H., Aziz‐Ahari, A., Shokrollahi, M. R., Pourakbari, B., Mahmoudi, S., & Movahedi, Z. (2020) · Journal of Microbiology Immunology and Infection · doi:10.1016/j.jmii.2020.07.019 · Cited by 33
“In the context of typical clinical presentation with COVID-19, CT imaging may be strongly helpful for suspicious to COVID-19 infection despite negative RT-PCR results.(6,15) However, the CT imaging in children differ from what has been reported until now.”
MethodCoSinGAN: Learning COVID-19 Infection Segmentation from a Single Radiological Image
Zhang, P., Zhong, Y., Deng, Y., Tang, X., & Li, X. (2020) · Diagnostics · doi:10.3390/diagnostics10110901 · Cited by 33
“Meanwhile, the current clinical experience implies RT-PCR has a low sensitivity [7–9], especially in the early outbreak of COVID-19.”
BackgroundMethodInfluentialIt’s not over until it’s over: the chameleonic behavior of COVID-19 over a six-day period
Fichera, G., Stramare, R., Conti, G. D., Motta, R., & Giraudo, C. (2020) · La radiologia medica · doi:10.1007/s11547-020-01203-0 · Cited by 32
La radiología en el diagnóstico de la neumonía por SARS-CoV-2 (COVID-19)
Sánchez-Oro, R., Nuez, J. P. T., & Martínez-Sanz, G. (2020) · Medicina Clínica · doi:10.1016/j.medcli.2020.03.004 · Cited by 32
“La TCT obtuvo en estos estudios muy buenos resultados, observándose que los hallazgos patológicos de la TCT pueden apa-recer incluso antes que los síntomas 7,12,13 y ser diagnósticos en pacientes con falsos negativos iniciales en la RT-PCR 7,8,14 .”
Jiang, Z.-Z., He, C., Wang, D., Shen, H.-L., Sun, J.-L., Gan, W.-N., Lu, J.-Y., & Liu, X. (2020) · Medical Science Monitor · doi:10.12659/msm.924582 · Cited by 33
Molecular and Serological Assays for SARS-CoV-2: Insights from Genome and Clinical Characteristics
Shi, J., Han, D., Zhang, R., Li, J., & Zhang, R. (2020) · Clinical Chemistry · doi:10.1093/clinchem/hvaa122 · Cited by 32
Orlandi, M., Lepri, G., Bruni, C., Wang, Y., Bartoloni, A., Zammarchi, L., Cometi, L., Guiducci, S., Matucci‐Cerinic, M., & Bellando-Randone, S. (2020) · Clinical Rheumatology · doi:10.1007/s10067-020-05193-2 · Cited by 33
Gao, Z., Xu, Y., Guo, Y., Xu, D., Zhang, L., Wang, X., Sun, C., Qiu, S., & Ma, K. (2020) · Infection Genetics and Evolution · doi:10.1016/j.meegid.2020.104494 · Cited by 32
Meiler, S., Schaible, J., Poschenrieder, F., Scharf, G., Zeman, F., Rennert, J., Pregler, B., Kleine, H., Stroszczynski, C., Zorger, N., et al. (2020) · European Journal of Radiology · doi:10.1016/j.ejrad.2020.109256 · Cited by 32
Typical CT findings of COVID-19 pneumonia in patients presenting with repetitive negative RT-PCR
Brogna, B., Bignardi, E., Brogna, C., Alberigo, M., Grappone, M., Megliola, A., Salvatore, P., Fontanella, G., Mazza, E. M., & Musto, L. (2020) · Radiography · doi:10.1016/j.radi.2020.09.012 · Cited by 33
A Deep-Learning Diagnostic Support System for the Detection of COVID-19 Using Chest Radiographs
Fontanellaz, M., Ebner, L., Huber, A. T., Peters, A. A., Loebelenz, L. I., Hourscht, C., Klaus, J. B., Munz, J., Ruder, T. D., Drakopoulos, D., et al. (2020) · Investigative Radiology · doi:10.1097/rli.0000000000000748 · Cited by 35
Association of AI quantified COVID-19 chest CT and patient outcome
Fang, X., Krüger, U., Homayounieh, F., Chao, H., Zhang, J., Digumarthy, S. R., Arru, C. D., Kalra, M. K., & Yan, P. (2021) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-020-02299-5 · Cited by 32
Kutlu, Y., & CAMGÖZLÜ, Y. (2021) · Natural and Engineering Sciences · doi:10.28978/nesciences.868087 · Cited by 33
“The symptoms of disease can be detected in radiological images of patients even if test result was negative (Kanne et al., 2020; Xie et al., 2020).”
BackgroundCOVID-19 pneumonia: A review of typical radiological characteristics
Arróspide, M. C., Martínez-Besteiro, E., Couñago, F., & Landete, P. (2021) · World Journal of Radiology · doi:10.4329/wjr.v13.i10.327 · Cited by 34
Hemamalini, V., Anand, L. G., Nachiyappan, S., Geeitha, S., Motupalli, V. R., Kumar, R., Ahilan, A., & Rajesh, M. (2022) · Measurement · doi:10.1016/j.measurement.2022.111054 · Cited by 32
“Though the usage of CT and X-rays explores some pathological solutions, the visibility of the images does not lead to the proper diagnosis of disease for further treatment, and the spread of infection are not reported due to abnormal pattern [55].”
BackgroundWu, F., Zhang, W., Zhang, L., Wang, D., & Wan, Y. (2020) · British Journal of Hospital Medicine · doi:10.12968/hmed.2020.0156 · Cited by 31
Detecting COVID-19 Patients in X-Ray Images Based on MAI-Nets
Wang, W., Huang, X. M., Li, J., Zhang, P., & Wang, X. (2021) · International Journal of Computational Intelligence Systems · doi:10.2991/ijcis.d.210518.001 · Cited by 31
Clinical and CT features of the COVID-19 infection: comparison among four different age groups
Li, W., Fang, Y., Liao, J., Yu, W., Yao, L., Cui, H., Zeng, X., Li, S., & Huang, C. (2020) · European Geriatric Medicine · doi:10.1007/s41999-020-00356-5 · Cited by 31
Chest CT findings in patients with coronavirus disease 2019 (COVID-19): a comprehensive review
Li, J., Yan, R., Zhai, Y., Qi, X., & Lei, J. (2020) · Diagnostic and Interventional Radiology · doi:10.5152/dir.2020.20212 · Cited by 31
Intracranial Hemorrhage in COVID-19 Patients
Mishra, S., Choueka, M., Wang, Q., Hu, C., Visone, S., Silver, M. P., Stein, E. G., Levine, S. R., & Wang, Q. T. (2021) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2021.105603 · Cited by 31
Adnan, N., Khandker, S. S., Haq, M. A., Chaity, M. A., Khalek, A., Nazim, A. Q., Kaitsuka, T., Tomizawa, K., Mie, M., Kobatake, E., et al. (2021) · Expert Review of Anti-infective Therapy · doi:10.1080/14787210.2021.1976144 · Cited by 31
Saygılı, A. (2021) · Arabian Journal for Science and Engineering · doi:10.1007/s13369-021-06240-z · Cited by 31
Bao, G., Chen, H., Liu, T., Gong, G., Yin, Y., Wang, L., & Wang, X. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.108499 · Cited by 31
Ahmad, M. I., Sadiq, S., Eshmawi, A. A., Alluhaidan, A. S., Umer, M., Ullah, S., & Nappi, M. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105418 · Cited by 35
A COVID-19 medical image classification algorithm based on Transformer
Ren, K., Hong, G., Chen, X., & Wang, Z. (2023) · Scientific Reports · doi:10.1038/s41598-023-32462-2 · Cited by 31
Cury, R. C., Megyeri, I., Lindsey, T., Macedo, R., Batlle, J. C., Kim, S., Baker, B., Harris, R. J., & Clark, R. H. (2021) · Radiology Cardiothoracic Imaging · doi:10.1148/ryct.2021200596 · Cited by 31
Ghodake, G. S., Shinde, S. K., Kadam, A. A., Saratale, R. G., Saratale, G. D., Syed, A., Elgorban, A. M., Marraiki, N., & Kim, D.-Y. (2021) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2021.112969 · Cited by 31
Texture feature-based machine learning classifier could assist in the diagnosis of COVID-19
Wu, Z., Li, L., Jin, R., Liang, L., Hu, Z., Tao, L., Han, Y. K., Feng, W., Zhou, D., Li, W., et al. (2021) · European Journal of Radiology · doi:10.1016/j.ejrad.2021.109602 · Cited by 30
“CT examination has been used to evaluate the pulmonary condition of those suspected SARS-CoV-2 infections [8].”
Usefulness of Lung Ultrasound in Paediatric Respiratory Diseases
Sansone, F., Attanasi, M., Filippo, P. D., Papa, G. F. S., Pillo, S. D., & Chiarelli, F. (2021) · Diagnostics · doi:10.3390/diagnostics11101783 · Cited by 30
“The gold standard for COVID-19 pneumonia assessment in adult patients is a chest CT scan, but this imaging technique has been discouraged in children, who present generally with milder signs and symptoms [73,74].”
BackgroundKoupaei, M., Mohamadi, M. H., Yashmi, I., Shahabi, A. H., Shabani, A. H., Heidary, M., & Khoshnood, S. (2022) · Journal of Clinical Laboratory Analysis · doi:10.1002/jcla.24402 · Cited by 30
“05) 11 Hypoxia 2/10 (20) 9 Skin lesions 8/41 (19.”
Improving COVID-19 CT classification of CNNs by learning parameter-efficient representation
Xu, Y., Lam, H., Jia, G., Jiang, J., Liao, J., & Bao, X. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106417 · Cited by 31
Chest CT findings and clinical features of coronavirus disease 2019 in children.
Zheng, Z., Xie, X., Huang, W., Zhao, W., Yu, Q., & Liu, J. (2020) · PubMed · doi:10.11817/j.issn.1672-7347.2020.200206 · Cited by 29
Self-citationChung, S. J., Tan, E. K., Kee, T. Y. S., Krishnamoorthy, T. L., Phua, G. C., Sewa, D. W., Ong, B., Tan, T. E., Sivathasan, C., Gan, H. L. V., et al. (2020) · Transplantation Direct · doi:10.1097/txd.0000000000001002 · Cited by 29
Hospital infection and COVID-19: Do not put all your eggs on the “swab” tests
Chirico, F., Nucera, G., & Magnavita, N. (2020) · Infection Control and Hospital Epidemiology · doi:10.1017/ice.2020.254 · Cited by 29
AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs
Arora, R., Bansal, V., Buckchash, H., Kumar, R., Sahayasheela, V. J., Narayanan, N., Pandian, G. N., & Raman, B. (2021) · Physical and Engineering Sciences in Medicine · doi:10.1007/s13246-021-01060-9 · Cited by 32
“Because of the low sensitivity of the RT-PCR test, even with the negative results, the symptoms can be elevated with the radiological screening of the images [11; 12].”
BackgroundZhang, Y., Yang, W., Liu, D., Cao, Y., Zheng, Y.-Y., Han, Y., Jin, R., Han, Y. K., Wang, X., Pan, A., et al. (2020) · Translational Lung Cancer Research · doi:10.21037/tlcr-20-892 · Cited by 27
Al-Falluji, R. A., Katheeth, Z. D., & Alathari, B. (2020) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2020.013232 · Cited by 29
“Due to the lack of RT-PCR tests in many countries, the symptoms are found through the examination of radiological images of the patients [2,3].”
BackgroundWang, L., Kelly, B. S., Lee, E. H., Wang, H., Zheng, J., Zhang, W., Halabi, S. S., Liu, J., Tian, Y., Han, B., et al. (2021) · European Journal of Radiology · doi:10.1016/j.ejrad.2021.109552 · Cited by 29
“In addition to the recommended viral nucleic acid real-time reverse transcriptase-polymerase chain reaction (RT-PCR) test, the value of radiological images for diagnosis of COVID-19 has been verified [2,3].”
Self-citationFarghaly, S., & Makboul, M. (2021) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-021-00408-1 · Cited by 30
Ramanujam, A., Almodóvar, S., & Botte, G. G. (2021) · Processes · doi:10.3390/pr9071236 · Cited by 32
“However, antibody-based testing techniques may not detect these infections at early phases [15].”
BackgroundAn Overview of Supervised Machine Learning Methods and Data Analysis for COVID-19 Detection
Kouanou, A. T., Attia, T. M., Feudjio, C., Djeumo, A. F., Mouelas, A. N., Nzogang, M. P., Tchapga, C. T., & Tchiotsop, D. (2021) · Journal of Healthcare Engineering · doi:10.1155/2021/4733167 · Cited by 24
“In [16, 17], authors have shown that chest CTs are highly sensitive to the diagnosis of COVID-19.”
BackgroundWITHDRAWN: Clinical and CT imaging features of 2019 novel coronavirus disease (COVID-19)
Zhu, Y., Liu, Y.-L., Li, Z., Kuang, J.-Y., Li, X., Yang, Y.-Y., & Feng, S. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.02.022 · Cited by 29
RetractedElli, L., Rimondi, A., Scaramella, L., Topa, M., Vecchi, M. L., Mangioni, D., Gori, A., & Penagini, R. (2020) · Digestive and Liver Disease · doi:10.1016/j.dld.2020.04.018 · Cited by 28
“Because of overall high specificity, patients with positive RT-PCR should always be considered as Covid-19 [5, 32] .”
The Virological, Immunological, and Imaging Approaches for COVID-19 Diagnosis and Research
Tan, A. S., Nerurkar, S. N., Tan, W. C. C., Goh, D. L. M., Lai, C. P. T., & Yeong, J. P.-S. (2020) · SLAS TECHNOLOGY · doi:10.1177/2472630320950248 · Cited by 28
Holborow, A., Asad, H., Porter, L., Tidswell, P., Johnston, C., Blyth, I., Bone, A., & Healy, B. (2020) · Clinical Medicine · doi:10.7861/clinmed.2020-0555 · Cited by 28
Assisting scalable diagnosis automatically via CT images in the combat against COVID-19
Liu, B., Liu, P., Dai, L., Yang, Y.-L., Xie, P., Tan, Y., Du, J., Shan, W., Zhao, C., Zhong, Q., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-83424-5 · Cited by 28
Ahmad, F., Khan, M. U. G., & Javed, K. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104401 · Cited by 29
Prediction of COVID-19 with Computed Tomography Images using Hybrid Learning Techniques
Perumal, V., Narayanan, V., & Rajasekar, S. J. S. (2021) · Disease Markers · doi:10.1155/2021/5522729 · Cited by 29
“RT-PCR is known to be the standard testing tool but has produced false negative rates in recent studies [5, 6] at the early stages.”
BackgroundKaram, M., Althuwaikh, S., Alazemi, M., Abul, A., Hayre, A., Alsaif, A., & Barlow, G. D. (2021) · JRSM Open · doi:10.1177/20542704211011837 · Cited by 29
Erdaw, Y., & Tachbele, E. (2021) · International Journal of General Medicine · doi:10.2147/ijgm.s325609 · Cited by 28
Computed tomography scan in COVID-19: a systematic review and meta-analysis
Sharif, P. M., Nematizadeh, M., Saghazadeh, M., Saghazadeh, A., & Rezaei, N. (2022) · Polish Journal of Radiology · doi:10.5114/pjr.2022.112613 · Cited by 29
“These findings are also in favour of the distribution patterns proposed previously [73-76].”
Li, F., Lu, X., & Yuan, J. (2021) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2021.3134270 · Cited by 28
AdaD-FNN for Chest CT-Based COVID-19 Diagnosis
Yao, X., Zhu, Z., Kang, C., Wang, S., Górriz, J. M., & Zhang, Y. (2022) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2022.3174868 · Cited by 29
Khanna, N. N., Maindarkar, M. A., Puvvula, A., Paul, S., Bhagawati, M., Ahluwalia, P., Ruzsa, Z., Sharma, A., Munjral, S., Kolluri, R., et al. (2022) · Journal of Cardiovascular Development and Disease · doi:10.3390/jcdd9080268 · Cited by 28
COVID-19 detection from chest CT images using optimized deep features and ensemble classification
Hossain, M. M., Walid, M. A. A., Galib, S. M. S., Azad, M. M., Rahman, W., Shafi, A. S. M., & Rahman, M. M. (2024) · Systems and Soft Computing · doi:10.1016/j.sasc.2024.200077 · Cited by 28
Zheng, Z., Yao, Z., Wu, K., & Zheng, J. (2020) · Journal of Clinical Virology · doi:10.1016/j.jcv.2020.104396 · Cited by 27
“[56] reported five patients with SARS-CoV-2 infection who had initial negative RT-PCR results, but typical CT scan showed findings such as GGO or consolidation.”
InfluentialAllergy clinics in times of the SARS-CoV-2 pandemic: an integrated model
Malipiero, G., Heffler, E. M., Pelaia, C., Puggioni, F., Racca, F., Ferri, S., Spinello, L., Merigo, M., Lamacchia, D., Cataldo, G., et al. (2020) · Clinical and Translational Allergy · doi:10.1186/s13601-020-00333-y · Cited by 27
“The first and obvious measure is quarantining of infected individuals, which is nonetheless limited by the challenge of identifying and isolating asymptomatic individuals and the high false negative rate of microbiological screening tests [5].”
BackgroundBentivegna, E., Luciani, M., Spuntarelli, V., Speranza, M. L., Guerritore, L., Sentimentale, A., & Martelletti, P. (2020) · SN Comprehensive Clinical Medicine · doi:10.1007/s42399-020-00383-0 · Cited by 27
Recent advances in the nucleic acid-based diagnostic tool for coronavirus
Prabhakar, P. K., & Lakhanpal, J. (2020) · Molecular Biology Reports · doi:10.1007/s11033-020-05889-3 · Cited by 27
“In the case of microarray, its cost limits its application commonly in the detection of SARS-CoV-2.”
MethodInfluentialCai, Q., Du, S., Si, G., Huang, G., Zheng, Z., Li, S., Wang, X., Li, P., Lv, P., Hou, G., et al. (2020) · BMC Medical Imaging · doi:10.1186/s12880-020-00521-z · Cited by 27
“Chest CT exams are useful in supplementary diagnosis of RT-PCR tests [5-7], evaluating disease stages [2,3,8,9] and severity [10-12].”
Laboratory Diagnosis of COVID-19
Asgharzadeh, M., Valiollahzadeh, M. R., Poor, B. M., Kafil, H. S., Asgharzadeh, V., Vegari, A., Pourostadi, M., Sanaat, Z., & Rashedi, J. (2020) · Clinical Pulmonary Medicine · doi:10.1097/cpm.0000000000000374 · Cited by 29
Ma, I. W. Y., Hussain, A., Wagner, M. S., Walker, B., Chee, A. C., Arishenkoff, S., Buchanan, B. M., Liu, R., Mints, G., Wong, T., et al. (2020) · Journal of Ultrasound in Medicine · doi:10.1002/jum.15571 · Cited by 27
How to choose the right real-time RT-PCR primer sets for the SARS-CoV-2 genome detection?
Anantharajah, A., Helaers, R., Defour, J., Olivé, N., Kabera, F., Croonen, L., Deldime, F., Vaerman, J.-L., Barbée, C., Bodéus, M., et al. (2021) · Journal of Virological Methods · doi:10.1016/j.jviromet.2021.114197 · Cited by 27
“…(CT) may reveal pulmonary abnormalities consistent with COVID-19, including ground-glass opacities, multifocal patchy consolidation, and/or interstitial changes with a peripheral distribution, even in patients with negative RT-qPCR results (Huang et al., 2020; Ai et al., 2020; Xie et al., 2020).”
LBP-based information assisted intelligent system for COVID-19 identification
Maheshwari, S., Sharma, R. R., & Kumar, M. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104453 · Cited by 27
“However, the symptoms of COVID-19 are noticed in different radiological examinations [17,18].”
Elsharkawy, M., Sharafeldeen, A., Taher, F., Shalaby, A. M., Soliman, A., Mahmoud, A. H., Ghazal, M. A., Khalil, A., Alghamdi, N. S., Razek, A. A. K. A., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-91305-0 · Cited by 28
Improved 3D U-Net for COVID-19 Chest CT Image Segmentation
Zheng, R., Zheng, Y., & Dongye, C. (2021) · Scientific Programming · doi:10.1155/2021/9999368 · Cited by 27
Generalizability assessment of COVID-19 3D CT data for deep learning-based disease detection
Fallahpoor, M., Chakraborty, S., Heshejin, M. T., Chegeni, H., Horry, M. J., & Pradhan, B. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105464 · Cited by 28
“Therefore, it has been proposed that chest CT could potentially be employed as the primary diagnostic modality for examining patients with COVID-19 [18].”
COVID-19 Detection from Chest X-ray Images Based on Deep Learning Techniques
Mathesul, S., Swain, D., Satapathy, S. K., Rambhad, A., Acharya, B., Gerogiannis, V. C., & Kanavos, A. (2023) · Algorithms · doi:10.3390/a16100494 · Cited by 27
Emerging Evidence for Neuropsycho-Consequences of COVID-19
Li, J., Long, X., Zhang, Q., Fang, X., Fang, F., Lv, X., Zhang, D., Sun, Y., Li, N., Hu, S., et al. (2020) · Current Neuropharmacology · doi:10.2174/1570159x18666200507085335 · Cited by 26
“The most characteristic symptom of NCP is respiratory distress, with a typical chest computer tomography (CT) finding of ground-glass opacity, similar to that of SARS [4].”
BackgroundWong, M. D., Thai, T., Li, Y., & Liu, H. (2020) · Experimental Biology and Medicine · doi:10.1177/1535370220938315 · Cited by 31
“All patients exhibited chest CTs with GGOs and/or mixed GGOs and consolidation.(33) A third study reported similar findings, with 97% sensitivity by the initial CT scan, as compared to the initial rRT-PCR sensitivity of 83.”
ResultA COVID-19 patient with multiple negative results for PCR assays outside Wuhan, China: a case report
Chen, L.-D., Li, H., Ye, Y.-M., Wu, Z., Huang, Y.-P., Zhang, W.-L., & Lin, L. (2020) · BMC Infectious Diseases · doi:10.1186/s12879-020-05245-7 · Cited by 26
Liu, N., He, G., Yang, X., Chen, J., Wu, J., Ma, M., Lu, W., Li, Q., Cheng, T., & Huang, X. (2020) · BMC Medical Imaging · doi:10.1186/s12880-020-00491-2 · Cited by 25
“Chest CT may be helpful for early diagnosis, especially when a person is suspected with COVID-19, but reverse transcription-polymerase chain reaction (RT-PCR) screening is negative[9-12].”
BackgroundAlyami, M. H., Alyami, H. S., & Warraich, A. (2020) · Saudi Pharmaceutical Journal · doi:10.1016/j.jsps.2020.09.014 · Cited by 26
“These tests are normally able to detect the relevant antibodies ten days after the disease develops (Mohd et al., 2016; Xie et al., 2020).”
Deepika, S., Venkatesan, A., Mahesh, V. G. V., & Raj, A. N. J. (2020) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22525 · Cited by 27
“The duration of the test is too long and the result of RT-PCR is affected by sampling errors and low viral load.(6) The antigen test is designed to detect the spike protein that is responsible for facilitating the entry of virus into the human cell.”
BackgroundSARS-CoV-2 Infection and the COVID-19 Pandemic Emergency: The Importance of Diagnostic Methods
Ciotti, M., Benedetti, F., Zella, D., Angeletti, S., Ciccozzi, M., & Bernardini, S. (2021) · Chemotherapy · doi:10.1159/000515343 · Cited by 30
Automated Detection of COVID-19 Using Deep Learning Approaches with Paper-Based ECG Reports
Bassiouni, M. M., Hegazy, I., Rizk, N. J., El‐Dahshan, E. A., & Salem, A.-B. M. (2022) · Circuits Systems and Signal Processing · doi:10.1007/s00034-022-02035-1 · Cited by 26
Sadik, F., Dastider, A. G., Subah, M. R., Mahmud, T., & Fattah, S. A. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.105806 · Cited by 25
Punitha, S. C., Stephan, T., Kannan, R., Mahmud, M., Kaiser, M. S., & Belhouari, S. B. (2023) · IEEE Access · doi:10.1109/access.2023.3236812 · Cited by 26
MSCCov19Net: multi-branch deep learning model for COVID-19 detection from cough sounds
Ulukaya, S., Sarıca, A. A., Erdem, O., & Karaali, A. (2023) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-023-02803-4 · Cited by 27
“While RT-PCR results are negative, results confirming ground-glass symptoms of COVID-19 have been reported in CT results [54].”
ResultHao, W., & Li, M. (2020) · Journal of Infection · doi:10.1016/j.jinf.2020.02.008 · Cited by 25
Huang, E. P., Sung, C., Chen, C., Fan, C., Lai, P., & Huang, Y. (2020) · Critical Care · doi:10.1186/s13054-020-02908-4 · Cited by 25
“Only 4 studies screened from 372 relevant articles were eligible [2, [4] [5] [6] .”
BackgroundAdded value of chest computed tomography in suspected COVID-19: an analysis of 239 patients
Korevaar, D. A., Kootte, R. S., Smits, L. P., van den Aardweg, J. G., Bonta, P. I., Schinkel, J., Vigeveno, R. M., van den Berk, I. A. H., Scheerder, M. J., Lemkes, B. A., et al. (2020) · European Respiratory Journal · doi:10.1183/13993003.01377-2020 · Cited by 24
Jiang, Y., Guo, D., Li, C., Chen, T., & Li, R. (2020) · Radiology of Infectious Diseases · doi:10.1016/j.jrid.2020.05.001 · Cited by 26
“As illustrated in Tables 2 and 3, the CT lesion extent and density scores were determined based on the anatomic distribution and density of lung lesions with reference to the reported semi-quantitative score system [12,13].”
Luca, D. D., Ravà, L., Nadel, S., Tissières, P., Gawronski, O., Perkins, E., Chidini, G., & Tingay, D. G. (2020) · European Journal of Pediatrics · doi:10.1007/s00431-020-03690-9 · Cited by 25
“RT-PCR false negative may account for up to 30% of tests [29], and this, together with the very small sample size, does not allow us to draw any conclusion.”
BackgroundMalek‐Hosseini, S. A., Nikoupour, H., Gholami, S., Shamsaeefar, A., Arasteh, P., Kazemi, K., Dehghani, M., Eghlimi, H., Shahraki, H. R., Roozbeh, J., et al. (2020) · Transplantation · doi:10.1097/tp.0000000000003470 · Cited by 25
“Diagnosis of COVID-19 was done based on a combination of polymerase chain reaction (PCR) of nasopharyngeal swabs, chest CT scan, chest radiography, and clinical symptoms.(11-14) All the patients had either chest CT scan or PCR confirmation for diagnosis of COVID-19 in our series.”
MethodSheervalilou, R., Shirvaliloo, M., Sargazi, S., Shirvalilou, S., Shahraki, O., Pilehvar‐Soltanahmadi, Y., Sarhadi, A., Nazarlou, Z., Ghaznavi, H., & Khoei, S. (2021) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-021-11197-y · Cited by 25
“There are accounts of certain false-negative reports by RT-PCR for cases that had already been confirmed to have SARS-CoV-2 infection (Xie et al. 2020).”
BackgroundDeif, M. A., Hammam, R. E., & Solyman, A. (2021) · International journal of intelligent engineering and systems · doi:10.22266/ijies2021.0430.16 · Cited by 25
Çolak, Ş., Yavuz, B. G., Yavuz, M., Özçelik, B., Öner, M., Özgültekin, A., & Şenbayrak, S. (2021) · International Journal of Clinical Practice · doi:10.1111/ijcp.14321 · Cited by 26
Johri, S., Goyal, M., Jain, S., Baranwal, M., Kumar, V., & Upadhyay, R. (2021) · International Journal of Imaging Systems and Technology · doi:10.1002/ima.22613 · Cited by 25
Up State of the SARS-COV-2 Spike Homotrimer Favors an Increased Virulence for New Variants
Giron, C. C., Laaksonen, A., & da Silva, F. L. B. (2021) · Frontiers in Medical Technology · doi:10.3389/fmedt.2021.694347 · Cited by 25
“For instance, at pH 7, 1Gelec is equal to −61 (4), −69 (8), and −66 (9) kJ/mol, respectively, for DDD, DUU, and UDD.”
Rapid Screening of COVID-19 Directly from Clinical Nasopharyngeal Swabs Using the MasSpec Pen
Garza, K. Y., Silva, A., da Rosa, J. R., Keating, M. F., Povilaitis, S. C., Spradlin, M., Sanches, P. H. G., Moura, A. V., Marrero-Gutiérrez, J., Lin, J. Q., et al. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c01937 · Cited by 26
Murugan, C., Ramamoorthy, S., Kuppuswamy, G. P., Murugan, R. K., Sivalingam, Y., & Sundaramurthy, A. (2021) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2021.10.144 · Cited by 28
Metadata
- Authors
- Xie, X., Zhong, Z., Zhao, W., Zheng, C., Wang, F., & Liu, J.
- Affiliations
- Central South University (CN)
- Corresponding author
- Liu, Jun
- Venue
- Radiology
- Published
- 2020-08
- Volume
- 296
- Issue
- 2
- Pages
- E41-E45
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- PMC
- PMC7233363
- OpenAlex
- W3006110666
- Cited by
- 1,960
- References
- 6
- Citations by year
- 2026: 16 · 2025: 24 · 2024: 75 · 2023: 136 · 2022: 282 · 2021: 575 · 2020: 850
- FWCI
- 60.46
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Radiology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Keywords
- COVID-19 pandemic, COVID-19 pneumonia, chest CT findings, ground-glass opacities, delayed diagnosis
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, COVID-19 Vaccines, COVID-19 Testing, Adult, Aged, False Negative Reactions, Female, Humans, Male, Middle Aged, Pneumonia, Viral, Radiographic Image Interpretation, Computer-Assisted, Tomography, X-Ray Computed, Reproducibility of Results, Coronavirus Infections, Clinical Laboratory Techniques, Reverse Transcriptase Polymerase Chain Reaction, Pandemics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review