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For: Belfiore MP, Urraro F, Grassi R, Giacobbe G, Patelli G, Cappabianca S, Reginelli A. Artificial intelligence to codify lung CT in Covid-19 patients. Radiol Med 2020;125:500-4. [PMID: 32367319 DOI: 10.1007/s11547-020-01195-x] [Cited by in Crossref: 72] [Cited by in F6Publishing: 77] [Article Influence: 24.0] [Reference Citation Analysis]
Number Citing Articles
1 Morais DFT, Fernandes G, Lima GD, Rodrigues JJPC. IoT-Based Wearable and Smart Health Device Solutions for Capnography: Analysis and Perspectives. Electronics 2023;12:1169. [DOI: 10.3390/electronics12051169] [Reference Citation Analysis]
2 Tzeng IS, Hsieh PC, Su WL, Hsieh TH, Chang SC. Artificial Intelligence-Assisted Chest X-ray for the Diagnosis of COVID-19: A Systematic Review and Meta-Analysis. Diagnostics (Basel) 2023;13. [PMID: 36832072 DOI: 10.3390/diagnostics13040584] [Reference Citation Analysis]
3 Giacobbe G, Granata V, Trovato P, Fusco R, Simonetti I, De Muzio F, Cutolo C, Palumbo P, Borgheresi A, Flammia F, Cozzi D, Gabelloni M, Grassi F, Miele V, Barile A, Giovagnoni A, Gandolfo N. Gender Medicine in Clinical Radiology Practice. J Pers Med 2023;13. [PMID: 36836457 DOI: 10.3390/jpm13020223] [Reference Citation Analysis]
4 Russo E, Tagliafico AS, Derchi L, Bignotti B, Tosto S, Martinoli C, Signori A, Brigati F, Viazzi F. Role of Renal Parenchyma Attenuation and Perirenal Fat Stranding in Chest CT of Hospitalized Patients with COVID-19. J Clin Med 2023;12. [PMID: 36769577 DOI: 10.3390/jcm12030929] [Reference Citation Analysis]
5 Polas MRH, Ahamed B, Rana MM. Artificial Intelligence and Blockchain Technology in the 4.0 IR Metaverse Era. Strategies and Opportunities for Technology in the Metaverse World 2023. [DOI: 10.4018/978-1-6684-5732-0.ch002] [Reference Citation Analysis]
6 Czibor S, Száraz L, Simon J, Dombai B, Gyebnár J, Szántó P, Magyar M, Dey D, Szakács L, Zsarnóczay E, Müller V, Merkely B, Györke T, Maurovich-horvat P. Comparison of morphological and metabolic imaging of COVID-19 pneumonia in a prospective clinical study.. [DOI: 10.21203/rs.3.rs-2209230/v1] [Reference Citation Analysis]
7 Mumuni AN, Hasford F, Udeme NI, Dada MO, Awojoyogbe BO. A SWOT analysis of artificial intelligence in diagnostic imaging in the developing world: making a case for a paradigm shift. Physical Sciences Reviews 2022;0. [DOI: 10.1515/psr-2022-0121] [Reference Citation Analysis]
8 Ji W, Sang C, Zhang X, Zhu K, Bo L. Personality, Preoperative Anxiety, and Postoperative Outcomes: A Review. Int J Environ Res Public Health 2022;19. [PMID: 36231463 DOI: 10.3390/ijerph191912162] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Trușculescu AA, Manolescu DL, Broască L, Ancușa VM, Ciocârlie H, Pescaru CC, Vaștag E, Oancea CI. Enhancing Imagistic Interstitial Lung Disease Diagnosis by Using Complex Networks. Medicina 2022;58:1288. [DOI: 10.3390/medicina58091288] [Reference Citation Analysis]
10 Hoang-thi T, Chassagnon G, Tran H, Le-dong N, Dinh-xuan AT, Revel M. How Artificial Intelligence in Imaging Can Better Serve Patients with Bronchial and Parenchymal Lung Diseases? JPM 2022;12:1429. [DOI: 10.3390/jpm12091429] [Reference Citation Analysis]
11 Broască L, Trușculescu AA, Ancușa VM, Ciocârlie H, Oancea CI, Stoicescu ER, Manolescu DL. A Novel Method for Lung Image Processing Using Complex Networks. Tomography 2022;8:1928-46. [PMID: 35894027 DOI: 10.3390/tomography8040162] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
12 Abdelgani Y, Makki QH, Ali H, Alzu'bi S. Intelligent Covid-19 Vaccine Supplychain Management System. 2022 13th International Conference on Information and Communication Systems (ICICS) 2022. [DOI: 10.1109/icics55353.2022.9811172] [Reference Citation Analysis]
13 Negroni D, Zagaria D, Paladini A, Falaschi Z, Arcoraci A, Barini M, Carriero A. COVID-19 CT Scan Lung Segmentation: How We Do It. J Digit Imaging 2022;35:424-31. [PMID: 35091874 DOI: 10.1007/s10278-022-00593-z] [Reference Citation Analysis]
14 Köksal M, Özkan E, Gülbay M, Aybar Bilir Y, Akinci E, Aypak A, Güner HR. COMPARISON OF INFECTED LUNG VOLUME OF COVID-19 PATIENTS AND THEIR CLINIC AND LABORATORY DATA. Kırıkkale Üniversitesi Tıp Fakültesi Dergisi 2022. [DOI: 10.24938/kutfd.1008677] [Reference Citation Analysis]
15 Albanesi M, Cozzi D, Cavigli E, Moroni C, Frezzetti G, Bartolini L, Miele V. Systemic Emergencies in COVID-19 Patient: A Pictorial Review. Tomography 2022;8:1041-51. [DOI: 10.3390/tomography8020084] [Reference Citation Analysis]
16 Ebrahimian S, Kalra MK, Agarwal S, Bizzo BC, Elkholy M, Wald C, Allen B, Dreyer KJ. FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies. Acad Radiol 2022;29:559-66. [PMID: 34969610 DOI: 10.1016/j.acra.2021.09.002] [Cited by in Crossref: 12] [Cited by in F6Publishing: 11] [Article Influence: 12.0] [Reference Citation Analysis]
17 Bruno F, Granata V, Cobianchi Bellisari F, Sgalambro F, Tommasino E, Palumbo P, Arrigoni F, Cozzi D, Grassi F, Brunese MC, Pradella S, di S Stefano MLM, Cutolo C, Di Cesare E, Splendiani A, Giovagnoni A, Miele V, Grassi R, Masciocchi C, Barile A. Advanced Magnetic Resonance Imaging (MRI) Techniques: Technical Principles and Applications in Nanomedicine. Cancers (Basel) 2022;14:1626. [PMID: 35406399 DOI: 10.3390/cancers14071626] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
18 Committeri U, Fusco R, Di Bernardo E, Abbate V, Salzano G, Maglitto F, Dell'Aversana Orabona G, Piombino P, Bonavolontà P, Arena A, Perri F, Maglione MG, Setola SV, Granata V, Iaconetta G, Ionna F, Petrillo A, Califano L. Radiomics Metrics Combined with Clinical Data in the Surgical Management of Early-Stage (cT1-T2 N0) Tongue Squamous Cell Carcinomas: A Preliminary Study. Biology (Basel) 2022;11. [PMID: 35336841 DOI: 10.3390/biology11030468] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
19 Shcherbak SG, Changalidi AI, Barbitoff YA, Anisenkova AY, Mosenko SV, Asaulenko ZP, Tsay VV, Polev DE, Kalinin RS, Eismont YA, Glotov AS, Garbuzov EY, Chernov AN, Klitsenko OA, Ushakov MO, Shikov AE, Urazov SP, Baranov VS, Glotov OS. Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients. Genes (Basel) 2022;13. [PMID: 35328087 DOI: 10.3390/genes13030534] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
20 Bartoli A, Fournel J, Maurin A, Marchi B, Habert P, Castelli M, Gaubert J, Cortaredona S, Lagier J, Million M, Raoult D, Ghattas B, Jacquier A. Value and prognostic impact of a deep learning segmentation model of COVID-19 lung lesions on low-dose chest CT. Research in Diagnostic and Interventional Imaging 2022;1:100003. [DOI: 10.1016/j.redii.2022.100003] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
21 Choudhury S, Chohan A, Dadhwal R, Vakil AP, Franco R, Taweesedt PT. Applications of artificial intelligence in common pulmonary diseases. Artif Intell Med Imaging 2022; 3(1): 1-7 [DOI: 10.35711/aimi.v3.i1.1] [Reference Citation Analysis]
22 Liu J, Wang Y, He G, Wang X, Sun M. Quantitative CT comparison between COVID-19 and mycoplasma pneumonia suspected as COVID-19: a longitudinal study. BMC Med Imaging 2022;22. [DOI: 10.1186/s12880-022-00750-4] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
23 Sarosh P, Parah SA, Bhat GM. An efficient image encryption scheme for healthcare applications. Multimed Tools Appl. [DOI: 10.1007/s11042-021-11812-0] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 3.0] [Reference Citation Analysis]
24 Zaeri N. AI Modeling to Combat COVID-19 Using CT Scan Imaging Algorithms and Simulations: A Study. Simulation Modeling 2022. [DOI: 10.5772/intechopen.99442] [Reference Citation Analysis]
25 Peng Y, Liu E, Peng S, Chen Q, Li D, Lian D. Using artificial intelligence technology to fight COVID-19: a review. Artif Intell Rev 2022;:1-37. [PMID: 35002010 DOI: 10.1007/s10462-021-10106-z] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
26 Chauhan NK, Asfahan S, Dutt N, Jalandra RN. Artificial intelligence in the practice of pulmonology: The future is now. Lung India 2022;39:1-2. [PMID: 34975044 DOI: 10.4103/lungindia.lungindia_692_21] [Reference Citation Analysis]
27 Shcherbak SG, Anisenkova AY, Mosenko SV, Glotov OS, Chernov AN, Apalko SV, Urazov SP, Garbuzov EY, Khobotnikov DN, Klitsenko OA, Minina EM, Asaulenko ZP. Basic Predictive Risk Factors for Cytokine Storms in COVID-19 Patients. Front Immunol 2021;12:745515. [PMID: 34858403 DOI: 10.3389/fimmu.2021.745515] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
28 Palumbo P, Palumbo MM, Bruno F, Picchi G, Iacopino A, Acanfora C, Sgalambro F, Arrigoni F, Ciccullo A, Cosimini B, Splendiani A, Barile A, Masedu F, Grimaldi A, Di Cesare E, Masciocchi C. Automated Quantitative Lung CT Improves Prognostication in Non-ICU COVID-19 Patients beyond Conventional Biomarkers of Disease. Diagnostics (Basel) 2021;11:2125. [PMID: 34829472 DOI: 10.3390/diagnostics11112125] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
29 Granata V, Ianniello S, Fusco R, Urraro F, Pupo D, Magliocchetti S, Albarello F, Campioni P, Cristofaro M, Di Stefano F, Fusco N, Petrone A, Schininà V, Villanacci A, Grassi F, Grassi R, Grassi R. Quantitative Analysis of Residual COVID-19 Lung CT Features: Consistency among Two Commercial Software. J Pers Med 2021;11:1103. [PMID: 34834455 DOI: 10.3390/jpm11111103] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
30 Coppola F, Faggioni L, Gabelloni M, De Vietro F, Mendola V, Cattabriga A, Cocozza MA, Vara G, Piccinino A, Lo Monaco S, Pastore LV, Mottola M, Malavasi S, Bevilacqua A, Neri E, Golfieri R. Human, All Too Human? An All-Around Appraisal of the "Artificial Intelligence Revolution" in Medical Imaging. Front Psychol 2021;12:710982. [PMID: 34650476 DOI: 10.3389/fpsyg.2021.710982] [Cited by in Crossref: 16] [Cited by in F6Publishing: 23] [Article Influence: 8.0] [Reference Citation Analysis]
31 Fusco R, Grassi R, Granata V, Setola SV, Grassi F, Cozzi D, Pecori B, Izzo F, Petrillo A. Artificial Intelligence and COVID-19 Using Chest CT Scan and Chest X-ray Images: Machine Learning and Deep Learning Approaches for Diagnosis and Treatment. J Pers Med 2021;11:993. [PMID: 34683133 DOI: 10.3390/jpm11100993] [Cited by in Crossref: 17] [Cited by in F6Publishing: 19] [Article Influence: 8.5] [Reference Citation Analysis]
32 Ardali Duzgun S, Durhan G, Basaran Demirkazik F, Irmak I, Karakaya J, Akpinar E, Gulsun Akpinar M, Inkaya AC, Ocal S, Topeli A, Ariyurek OM. AI-Based Quantitative CT Analysis of Temporal Changes According to Disease Severity in COVID-19 Pneumonia. J Comput Assist Tomogr 2021;45:970-8. [PMID: 34581706 DOI: 10.1097/RCT.0000000000001224] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
33 Reginelli A, Nardone V, Giacobbe G, Belfiore MP, Grassi R, Schettino F, Del Canto M, Grassi R, Cappabianca S. Radiomics as a New Frontier of Imaging for Cancer Prognosis: A Narrative Review. Diagnostics (Basel) 2021;11:1796. [PMID: 34679494 DOI: 10.3390/diagnostics11101796] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
34 Baratella E, Ruaro B, Marrocchio C, Starvaggi N, Salton F, Giudici F, Quaia E, Confalonieri M, Cova MA. Interstitial Lung Disease at High Resolution CT after SARS-CoV-2-Related Acute Respiratory Distress Syndrome According to Pulmonary Segmental Anatomy. J Clin Med 2021;10:3985. [PMID: 34501430 DOI: 10.3390/jcm10173985] [Cited by in Crossref: 22] [Cited by in F6Publishing: 25] [Article Influence: 11.0] [Reference Citation Analysis]
35 Arora G, Joshi J, Mandal RS, Shrivastava N, Virmani R, Sethi T. Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19. Pathogens 2021;10:1048. [PMID: 34451513 DOI: 10.3390/pathogens10081048] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 7.5] [Reference Citation Analysis]
36 Arora G, Joshi J, Mandal RS, Shrivastava N, Virmani R, Sethi T. Artificial Intelligence in Surveillance, Diagnosis, Drug Discovery and Vaccine Development against COVID-19. Pathogens 2021;10:1048. [PMID: 34451513 DOI: 10.3390/pathogens10081048] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
37 Caruso D, Pucciarelli F, Zerunian M, Ganeshan B, De Santis D, Polici M, Rucci C, Polidori T, Guido G, Bracci B, Benvenga A, Barbato L, Laghi A. Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia. Radiol Med 2021. [PMID: 34347270 DOI: 10.1007/s11547-021-01402-3] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 3.5] [Reference Citation Analysis]
38 Nardone V, Boldrini L, Grassi R, Franceschini D, Morelli I, Becherini C, Loi M, Greto D, Desideri I. Radiomics in the Setting of Neoadjuvant Radiotherapy: A New Approach for Tailored Treatment. Cancers (Basel) 2021;13:3590. [PMID: 34298803 DOI: 10.3390/cancers13143590] [Cited by in Crossref: 7] [Cited by in F6Publishing: 8] [Article Influence: 3.5] [Reference Citation Analysis]
39 Rathinam AK, Lee Y, Chek Ling DN, Singh R, Selvaratnam L, Pamidi N. Artificial Intelligence in Medicine: A review of challenges in implementation and disparity. 2021 IEEE International Conference on Health, Instrumentation & Measurement, and Natural Sciences (InHeNce) 2021. [DOI: 10.1109/inhence52833.2021.9537270] [Reference Citation Analysis]
40 Mousseaux E, Fayol A, Danchin N, Soulat G, Charpentier E, Livrozet M, Carves JB, Tea V, Salem FB, Chamandi C, Hulot JS, Puymirat E. Association between coronary artery calcifications and 6-month mortality in hospitalized patients with COVID-19. Diagn Interv Imaging 2021:S2211-5684(21)00169-8. [PMID: 34312110 DOI: 10.1016/j.diii.2021.06.007] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
41 Grassi R, Cappabianca S, Urraro F, Granata V, Giacobbe G, Magliocchetti S, Cozzi D, Fusco R, Galdiero R, Picone C, Belfiore MP, Reginelli A, Atripaldi U, Picascia O, Coppola M, Bignardi E, Grassi R, Miele V. Evolution of CT Findings and Lung Residue in Patients with COVID-19 Pneumonia: Quantitative Analysis of the Disease with a Computer Automatic Tool. J Pers Med 2021;11:641. [PMID: 34357108 DOI: 10.3390/jpm11070641] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
42 Singh K, Misra M, Yadav J. Artificial Intelligence and Machine Learning as a Tool for Combating COVID-19: A Case Study on Health-Tech Start-ups. 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) 2021. [DOI: 10.1109/icccnt51525.2021.9579950] [Reference Citation Analysis]
43 Elsharkawy M, Sharafeldeen A, Taher F, Shalaby A, Soliman A, Mahmoud A, Ghazal M, Khalil A, Alghamdi NS, Razek AAKA, Alnaghy E, El-Melegy MT, Sandhu HS, Giridharan GA, El-Baz A. Early assessment of lung function in coronavirus patients using invariant markers from chest X-rays images. Sci Rep 2021;11:12095. [PMID: 34103587 DOI: 10.1038/s41598-021-91305-0] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
44 Li T, Huang T, Guo C, Wang A, Shi X, Mo X, Lu Q, Sun J, Hui T, Tian G, Wang L, Yang J. Genomic variation, origin tracing, and vaccine development of SARS-CoV-2: A systematic review. Innovation (Camb) 2021;2:100116. [PMID: 33997827 DOI: 10.1016/j.xinn.2021.100116] [Cited by in Crossref: 25] [Cited by in F6Publishing: 31] [Article Influence: 12.5] [Reference Citation Analysis]
45 Singh R, Singh PK, Kumar R, Kabir MT, Kamal MA, Rauf A, Albadrani GM, Sayed AA, Mousa SA, Abdel-Daim MM, Uddin MS. Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19. Front Pharmacol 2021;12:652335. [PMID: 34054532 DOI: 10.3389/fphar.2021.652335] [Cited by in Crossref: 12] [Cited by in F6Publishing: 12] [Article Influence: 6.0] [Reference Citation Analysis]
46 Chrzan R, Bociąga-Jasik M, Bryll A, Grochowska A, Popiela T. Differences among COVID-19, Bronchopneumonia and Atypical Pneumonia in Chest High Resolution Computed Tomography Assessed by Artificial Intelligence Technology. J Pers Med 2021;11:391. [PMID: 34068751 DOI: 10.3390/jpm11050391] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
47 Moezzi M, Shirbandi K, Shahvandi HK, Arjmand B, Rahim F. The diagnostic accuracy of Artificial Intelligence-Assisted CT imaging in COVID-19 disease: A systematic review and meta-analysis. Inform Med Unlocked 2021;24:100591. [PMID: 33977119 DOI: 10.1016/j.imu.2021.100591] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
48 Maio F, Tari DU, Granata V, Fusco R, Grassi R, Petrillo A, Pinto F. Breast Cancer Screening during COVID-19 Emergency: Patients and Department Management in a Local Experience. J Pers Med 2021;11:380. [PMID: 34066425 DOI: 10.3390/jpm11050380] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
49 Charpentier E, Soulat G, Fayol A, Hernigou A, Livrozet M, Grand T, Reverdito G, Al Haddad J, Dang Tran KD, Charpentier A, Clement O, Hulot JS, Mousseaux E. Visual lung damage CT score at hospital admission of COVID-19 patients and 30-day mortality. Eur Radiol 2021. [PMID: 33914118 DOI: 10.1007/s00330-021-07938-2] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 4.5] [Reference Citation Analysis]
50 Giordano FM, Ippolito E, Quattrocchi CC, Greco C, Mallio CA, Santo B, D'Alessio P, Crucitti P, Fiore M, Zobel BB, D'Angelillo RM, Ramella S. Radiation-Induced Pneumonitis in the Era of the COVID-19 Pandemic: Artificial Intelligence for Differential Diagnosis. Cancers (Basel) 2021;13:1960. [PMID: 33921652 DOI: 10.3390/cancers13081960] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
51 D'Agostino V, Caranci F, Negro A, Piscitelli V, Tuccillo B, Fasano F, Sirabella G, Marano I, Granata V, Grassi R, Pupo D, Grassi R. A Rare Case of Cerebral Venous Thrombosis and Disseminated Intravascular Coagulation Temporally Associated to the COVID-19 Vaccine Administration. J Pers Med 2021;11:285. [PMID: 33917902 DOI: 10.3390/jpm11040285] [Cited by in Crossref: 47] [Cited by in F6Publishing: 52] [Article Influence: 23.5] [Reference Citation Analysis]
52 Nardone V, Reginelli A, Vinciguerra C, Correale P, Calvanese MG, Falivene S, Sangiovanni A, Grassi R, Di Biase A, Polifrone MA, Caraglia M, Cappabianca S, Guida C. Mood Disorder in Cancer Patients Undergoing Radiotherapy During the COVID-19 Outbreak. Front Psychol 2021;12:568839. [PMID: 33815186 DOI: 10.3389/fpsyg.2021.568839] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
53 Granata V, Fusco R, Setola SV, Galdiero R, Picone C, Izzo F, D'Aniello R, Miele V, Grassi R, Grassi R, Petrillo A. Lymphadenopathy after BNT162b2 Covid-19 Vaccine: Preliminary Ultrasound Findings. Biology (Basel) 2021;10:214. [PMID: 33799618 DOI: 10.3390/biology10030214] [Cited by in Crossref: 19] [Cited by in F6Publishing: 23] [Article Influence: 9.5] [Reference Citation Analysis]
54 Granata V, Fusco R, Izzo F, Venanzio Setola S, Coppola M, Grassi R, Reginelli A, Cappabianca S, Grassi R, Petrillo A. Covid-19 infection in cancer patients: the management in a diagnostic unit. Radiol Oncol 2021;55:121-9. [PMID: 33675200 DOI: 10.2478/raon-2021-0010] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
55 Tagliafico AS, Albano D, Torri L, Messina C, Gitto S, Bruno F, Barile A, Giovagnoni A, Miele V, Grassi R, Sconfienza LM. Impact of coronavirus disease 2019 (COVID-19) outbreak on radiology research: An Italian survey. Clin Imaging 2021;76:144-8. [PMID: 33601188 DOI: 10.1016/j.clinimag.2021.02.009] [Cited by in Crossref: 6] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
56 Revel MP. COVID-19 pneumonia: The fight must go on. Diagn Interv Imaging 2021;102:61-2. [PMID: 33494861 DOI: 10.1016/j.diii.2021.01.006] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
57 Raza K, Maryam, Qazi S. An Introduction to Computational Intelligence in COVID-19: Surveillance, Prevention, Prediction, and Diagnosis. Studies in Computational Intelligence 2021. [DOI: 10.1007/978-981-15-8534-0_1] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
58 Nain M, Sharma S, Chaurasia S. Pandemic Management Using Artificial Intelligence-Based Safety Measures. Advances in Medical Technologies and Clinical Practice 2021. [DOI: 10.4018/978-1-7998-7188-0.ch007] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
59 Al-emran M, Al-kabi MN, Marques G. A Survey of Using Machine Learning Algorithms During the COVID-19 Pandemic. Studies in Systems, Decision and Control 2021. [DOI: 10.1007/978-3-030-67716-9_1] [Cited by in Crossref: 4] [Article Influence: 2.0] [Reference Citation Analysis]
60 Prashant Nagpal, Junfeng Guo, Kyung Min Shin, Jae-Kwang Lim, Ki Beom Kim, Alejandro P Comellas, David W Kaczka, Samuel Peterson, Chang Hyun Lee, Eric A Hoffman. Quantitative CT imaging and advanced visualization methods: potential application in novel coronavirus disease 2019 (COVID-19) pneumonia. BJR Open 2021;3:20200043. [PMID: 33718766 DOI: 10.1259/bjro.20200043] [Cited by in Crossref: 9] [Cited by in F6Publishing: 9] [Article Influence: 4.5] [Reference Citation Analysis]
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