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For: Ong E, Wong MU, Huffman A, He Y. COVID-19 Coronavirus Vaccine Design Using Reverse Vaccinology and Machine Learning. Front Immunol 2020;11:1581. [PMID: 32719684 DOI: 10.3389/fimmu.2020.01581] [Cited by in Crossref: 69] [Cited by in F6Publishing: 140] [Article Influence: 34.5] [Reference Citation Analysis]
Number Citing Articles
1 Chen J, Li K, Zhang Z, Li K, Yu PS. A Survey on Applications of Artificial Intelligence in Fighting Against COVID-19. ACM Comput Surv 2022;54:1-32. [DOI: 10.1145/3465398] [Cited by in Crossref: 21] [Article Influence: 21.0] [Reference Citation Analysis]
2 Taheri G, Habibi M. Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning method. Appl Soft Comput 2022;128:109510. [PMID: 35992221 DOI: 10.1016/j.asoc.2022.109510] [Reference Citation Analysis]
3 Yi J, Zhang H, Mao J, Chen Y, Zhong H, Wang Y. Review on the COVID-19 pandemic prevention and control system based on AI. Eng Appl Artif Intell 2022;114:105184. [PMID: 35846728 DOI: 10.1016/j.engappai.2022.105184] [Reference Citation Analysis]
4 Nirmaladevi J, Vidhyalakshmi M, Edwin EB, Venkateswaran N, Avasthi V, Alarfaj AA, Hirad AH, Rajendran RK, Hailu T, Teekaraman Y. Deep Convolutional Neural Network Mechanism Assessment of COVID-19 Severity. BioMed Research International 2022;2022:1-14. [DOI: 10.1155/2022/1289221] [Reference Citation Analysis]
5 Baressi Šegota S, Lorencin I, Anđelić N, Musulin J, Štifanić D, Glučina M, Vlahinić S, Car Z. Applying Regressive Machine Learning Techniques in Determination of COVID-19 Vaccinated Patients’ Influence on the Number of Confirmed and Deceased Patients. Mathematics 2022;10:2925. [DOI: 10.3390/math10162925] [Reference Citation Analysis]
6 Kumar S, Kumar GS, Maitra SS, Malý P, Bharadwaj S, Sharma P, Dwivedi VD. Viral informatics: bioinformatics-based solution for managing viral infections. Brief Bioinform 2022:bbac326. [PMID: 35947964 DOI: 10.1093/bib/bbac326] [Reference Citation Analysis]
7 Park T, Hwang H, Moon S, Kang SG, Song S, Kim YH, Kim H, Ko EJ, Yoon SD, Kang SM, Hwang HS. Vaccines against SARS-CoV-2 variants and future pandemics. Expert Rev Vaccines 2022. [PMID: 35924678 DOI: 10.1080/14760584.2022.2110075] [Reference Citation Analysis]
8 Tobuse AJ, Ang CW, Yeong KY. Modern vaccine development via reverse vaccinology to combat antimicrobial resistance. Life Sciences 2022;302:120660. [DOI: 10.1016/j.lfs.2022.120660] [Reference Citation Analysis]
9 Chen Z, Zhang Y, Wang M, Islam MS, Liao P, Hu Y, Chen X. Humoral and Cellular Immune Responses of COVID-19 vaccines against SARS-Cov-2 Omicron variant: a systemic review. Int J Biol Sci 2022;18:4629-41. [PMID: 35874952 DOI: 10.7150/ijbs.73583] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
10 Du B, Guo Y, Li G, Zhu Y, Wang Y, Xi X. Non-structure protein ORF1ab (NSP8) in SARS-CoV-2 contains potential γδT cell epitopes. Front Microbiol 2022;13:936272. [DOI: 10.3389/fmicb.2022.936272] [Reference Citation Analysis]
11 Mortezaei Z, Mohammadian A, Tavallaei M. Variations of SARS-CoV-2 in the Iranian population and candidate putative drug-like compounds to inhibit the mutated proteins. Heliyon 2022;8:e09910. [PMID: 35847618 DOI: 10.1016/j.heliyon.2022.e09910] [Reference Citation Analysis]
12 Seyran M. Artificial intelligence and clinical data suggest the T cell-mediated SARS-CoV-2 nonstructural protein intranasal vaccines for global COVID-19 immunity. Vaccine 2022:S0264-410X(22)00821-0. [PMID: 35778279 DOI: 10.1016/j.vaccine.2022.06.052] [Reference Citation Analysis]
13 Huffman A, Ong E, Hur J, D'Mello A, Tettelin H, He Y. COVID-19 vaccine design using reverse and structural vaccinology, ontology-based literature mining and machine learning. Brief Bioinform 2022:bbac190. [PMID: 35649389 DOI: 10.1093/bib/bbac190] [Reference Citation Analysis]
14 Kumar A, Ladha A, Choudhury A, Ikbal AMA, Bhattacharjee B, Das T, Gupta G, Sharma C, Sarbajna A, Mandal SC, Choudhury MD, Ali N, Slama P, Rezaei N, Palit P, Tiwari ON. The chimera of S1 and N proteins of SARS-CoV-2: can it be a potential vaccine candidate for COVID-19? Expert Rev Vaccines 2022. [PMID: 35604776 DOI: 10.1080/14760584.2022.2081156] [Reference Citation Analysis]
15 Gao K, Wang R, Chen J, Cheng L, Frishcosy J, Huzumi Y, Qiu Y, Schluckbier T, Wei X, Wei GW. Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2. Chem Rev 2022. [PMID: 35594413 DOI: 10.1021/acs.chemrev.1c00965] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
16 Saravanan KA, Panigrahi M, Kumar H, Rajawat D, Nayak SS, Bhushan B, Dutt T. Role of genomics in combating COVID-19 pandemic. Gene 2022;823:146387. [PMID: 35248659 DOI: 10.1016/j.gene.2022.146387] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
17 Diaz-hernandez A, Gonzalez-vazquez MC, Arce-fonseca M, Rodríguez-morales O, Cedillo-ramirez ML, Carabarin-lima A. Consensus Enolase of Trypanosoma Cruzi: Evaluation of Their Immunogenic Properties Using a Bioinformatics Approach. Life 2022;12:746. [DOI: 10.3390/life12050746] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
18 Albalawi U, Mustafa M. Current Artificial Intelligence (AI) Techniques, Challenges, and Approaches in Controlling and Fighting COVID-19: A Review. Int J Environ Res Public Health 2022;19:5901. [PMID: 35627437 DOI: 10.3390/ijerph19105901] [Reference Citation Analysis]
19 Galetsi P, Katsaliaki K, Kumar S. The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19. Soc Sci Med 2022;301:114973. [PMID: 35452893 DOI: 10.1016/j.socscimed.2022.114973] [Reference Citation Analysis]
20 Asghar N, Mumtaz H, Syed AA, Eqbal F, Maharjan R, Bamboria A, Shrehta M. Safety, efficacy, and immunogenicity of COVID-19 vaccines; a systematic review. Immunological Medicine. [DOI: 10.1080/25785826.2022.2068331] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
21 Yadav D, Agarwal S, Pancham P, Jindal D, Agarwal V, Dubey PK, Jha SK, Mani S, Rachana, Dey A, Jha NK, Kesari KK, Singh M. Probing the Immune System Dynamics of the COVID-19 Disease for Vaccine Designing and Drug Repurposing Using Bioinformatics Tools. Immuno 2022;2:344-71. [DOI: 10.3390/immuno2020022] [Reference Citation Analysis]
22 Razi O, Tartibian B, Laher I, Govindasamy K, Zamani N, Rocha-rodrigues S, Suzuki K, Zouhal H. Multimodal Benefits of Exercise in Patients With Multiple Sclerosis and COVID-19. Front Physiol 2022;13:783251. [DOI: 10.3389/fphys.2022.783251] [Reference Citation Analysis]
23 Soraci L, Lattanzio F, Soraci G, Gambuzza ME, Pulvirenti C, Cozza A, Corsonello A, Luciani F, Rezza G. COVID-19 Vaccines: Current and Future Perspectives. Vaccines 2022;10:608. [DOI: 10.3390/vaccines10040608] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
24 Aileni M, Rohela GK, Jogam P, Soujanya S, Zhang B. Biotechnological Perspectives to Combat the COVID-19 Pandemic: Precise Diagnostics and Inevitable Vaccine Paradigms. Cells 2022;11:1182. [DOI: 10.3390/cells11071182] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
25 Fox S, Mcdermott J, Doherty E, Cooney R, Clifford E. Application of Neural Networks and Regression Modelling to Enable Environmental Regulatory Compliance and Energy Optimisation in a Sequencing Batch Reactor. Sustainability 2022;14:4098. [DOI: 10.3390/su14074098] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
26 Roland T, Böck C, Tschoellitsch T, Maletzky A, Hochreiter S, Meier J, Klambauer G. Domain Shifts in Machine Learning Based Covid-19 Diagnosis From Blood Tests. J Med Syst 2022;46. [DOI: 10.1007/s10916-022-01807-1] [Reference Citation Analysis]
27 Thakur S, Sasi S, Pillai SG, Nag A, Shukla D, Singhal R, Phalke S, Velu GSK. SARS-CoV-2 Mutations and Their Impact on Diagnostics, Therapeutics and Vaccines. Front Med (Lausanne) 2022;9:815389. [PMID: 35273977 DOI: 10.3389/fmed.2022.815389] [Cited by in Crossref: 6] [Cited by in F6Publishing: 13] [Article Influence: 6.0] [Reference Citation Analysis]
28 An H, Eun M, Yi J, Park J. CRESSP: a comprehensive pipeline for prediction of immunopathogenic SARS-CoV-2 epitopes using structural properties of proteins. Brief Bioinform 2022:bbac056. [PMID: 35226074 DOI: 10.1093/bib/bbac056] [Reference Citation Analysis]
29 Medeiros KS, Costa APF, Sarmento ACA, Freitas CL, Gonçalves AK. Side effects of COVID-19 vaccines: a systematic review and meta-analysis protocol of randomised trials. BMJ Open 2022;12:e050278. [PMID: 35210336 DOI: 10.1136/bmjopen-2021-050278] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
30 Biabani SAA, Tayyib NA. A Review on the Use of Machine Learning Against the Covid-19 Pandemic. Eng Technol Appl Sci Res 2022;12:8039-44. [DOI: 10.48084/etasr.4628] [Reference Citation Analysis]
31 Bacciu D, Girardi E, Maratea M, Sousa J. AI & COVID-19. IA 2022;15:45-53. [DOI: 10.3233/ia-210121] [Reference Citation Analysis]
32 Chang Z, Zhan Z, Zhao Z, You Z, Liu Y, Yan Z, Fu Y, Liang W, Zhao L. Application of artificial intelligence in COVID-19 medical area: a systematic review. J Thorac Dis 2021;13:7034-53. [PMID: 35070385 DOI: 10.21037/jtd-21-747] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
33 Bagabir S, Ibrahim NK, Bagabir H, Ateeq R. Covid-19 and Artificial Intelligence: Genome Sequencing, Drug Development and Vaccine discovery. Journal of Infection and Public Health 2022. [DOI: 10.1016/j.jiph.2022.01.011] [Cited by in Crossref: 4] [Article Influence: 4.0] [Reference Citation Analysis]
34 Grekousis G, Feng Z, Marakakis I, Lu Y, Wang R. Ranking the importance of demographic, socioeconomic, and underlying health factors on US COVID-19 deaths: A geographical random forest approach. Health & Place 2022. [DOI: 10.1016/j.healthplace.2022.102744] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
35 Rafi MO, Al-khafaji K, Sarker MT, Taskin-tok T, Rana AS, Rahman MS. Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods. RSC Adv 2022;12:4288-310. [DOI: 10.1039/d1ra06532g] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
36 Huang PC, Goru R, Huffman A, Yu Lin A, Cooke MF, He Y. Cov19VaxKB: A Web-based Integrative COVID-19 Vaccine Knowledge Base. Vaccine X 2021;:100139. [PMID: 34981039 DOI: 10.1016/j.jvacx.2021.100139] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
37 Li J, Huang Z, Lu S, Luo H, Tan Y, Ye P, Liu X, Wu Z, Wu C, Stalin A, Wang H, Liu Y, Shen L, Fan X, Zhang B, Yi J, Yao L, Xu Y, Wu J, Duan X. Exploring potential mechanisms of Suhexiang Pill against COVID-19 based on network pharmacology and molecular docking. Medicine (Baltimore) 2021;100:e27112. [PMID: 34941025 DOI: 10.1097/MD.0000000000027112] [Reference Citation Analysis]
38 Yan C, Feng X, Li G. From Drug Molecules to Thermoset Shape Memory Polymers: A Machine Learning Approach. ACS Appl Mater Interfaces 2021;13:60508-21. [PMID: 34878247 DOI: 10.1021/acsami.1c20947] [Reference Citation Analysis]
39 Ozger ZB, Cihan P. A novel ensemble fuzzy classification model in SARS-CoV-2 B-cell epitope identification for development of protein-based vaccine. Appl Soft Comput 2022;116:108280. [PMID: 34931117 DOI: 10.1016/j.asoc.2021.108280] [Reference Citation Analysis]
40 Darooneh AH, Przedborski M, Kohandel M. A novel statistical method predicts mutability of the genomic segments of the SARS-CoV-2 virus. QRB Discovery 2022;3. [DOI: 10.1017/qrd.2021.13] [Reference Citation Analysis]
41 Prasad K, Kumar V. Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2. Curr Res Pharmacol Drug Discov 2021;2:100042. [PMID: 34870150 DOI: 10.1016/j.crphar.2021.100042] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
42 Liu CH, Lu CH, Lin LT. Pandemic Strategies with Computational and Structural Biology against COVID-19: A Retrospective. Comput Struct Biotechnol J 2021. [PMID: 34900126 DOI: 10.1016/j.csbj.2021.11.040] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
43 Joshi G, Borah P, Thakur S, Sharma P, Mayank, Poduri R. Exploring the COVID-19 vaccine candidates against SARS-CoV-2 and its variants: where do we stand and where do we go? Hum Vaccin Immunother 2021;:1-27. [PMID: 34856868 DOI: 10.1080/21645515.2021.1995283] [Reference Citation Analysis]
44 Machado AS, Castelo PM, Capela E Silva F, Lamy E. Covid-19: Signs and symptoms related to the feeding behavior. Physiol Behav 2021;242:113605. [PMID: 34600920 DOI: 10.1016/j.physbeh.2021.113605] [Reference Citation Analysis]
45 Nguyen DC, Ding M, Pathirana PN, Seneviratne A. Blockchain and AI-Based Solutions to Combat Coronavirus (COVID-19)-Like Epidemics: A Survey. IEEE Access 2021;9:95730-53. [PMID: 34812398 DOI: 10.1109/ACCESS.2021.3093633] [Cited by in Crossref: 10] [Cited by in F6Publishing: 20] [Article Influence: 10.0] [Reference Citation Analysis]
46 Ma L, Li H, Lan J, Hao X, Liu H, Wang X, Huang Y. Comprehensive analyses of bioinformatics applications in the fight against COVID-19 pandemic. Comput Biol Chem 2021;95:107599. [PMID: 34773807 DOI: 10.1016/j.compbiolchem.2021.107599] [Reference Citation Analysis]
47 Lv H, Shi L, Berkenpas JW, Dao FY, Zulfiqar H, Ding H, Zhang Y, Yang L, Cao R. Application of artificial intelligence and machine learning for COVID-19 drug discovery and vaccine design. Brief Bioinform 2021;22:bbab320. [PMID: 34410360 DOI: 10.1093/bib/bbab320] [Cited by in F6Publishing: 9] [Reference Citation Analysis]
48 Tayara H, Abdelbaky I, To Chong K. Recent omics-based computational methods for COVID-19 drug discovery and repurposing. Brief Bioinform 2021;22:bbab339. [PMID: 34423353 DOI: 10.1093/bib/bbab339] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
49 He S, Leanse LG, Feng Y. Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases. Adv Drug Deliv Rev 2021;178:113922. [PMID: 34461198 DOI: 10.1016/j.addr.2021.113922] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 5.0] [Reference Citation Analysis]
50 Qian K, Schmitt M, Zheng H, Koike T, Han J, Liu J, Ji W, Duan J, Song M, Yang Z, Ren Z, Liu S, Zhang Z, Yamamoto Y, Schuller BW. Computer Audition for Fighting the SARS-CoV-2 Corona Crisis-Introducing the Multitask Speech Corpus for COVID-19. IEEE Internet Things J 2021;8:16035-46. [PMID: 35782182 DOI: 10.1109/JIOT.2021.3067605] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
51 Wang L, Zhang Y, Wang D, Tong X, Liu T, Zhang S, Huang J, Zhang L, Chen L, Fan H, Clarke M. Artificial Intelligence for COVID-19: A Systematic Review. Front Med (Lausanne) 2021;8:704256. [PMID: 34660623 DOI: 10.3389/fmed.2021.704256] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
52 Kaur J, Kaur P. Outbreak COVID-19 in Medical Image Processing Using Deep Learning: A State-of-the-Art Review. Arch Comput Methods Eng 2021;:1-32. [PMID: 34690493 DOI: 10.1007/s11831-021-09667-7] [Reference Citation Analysis]
53 Wang T, Chen Z, Shang Q, Ma C, Chen X, Xiao E. A Promising and Challenging Approach: Radiologists' Perspective on Deep Learning and Artificial Intelligence for Fighting COVID-19. Diagnostics (Basel) 2021;11:1924. [PMID: 34679622 DOI: 10.3390/diagnostics11101924] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
54 Almustafa KM. Covid19-Mexican-Patients' Dataset (Covid19MPD) Classification and Prediction Using Feature Importance. Concurr Comput 2021;:e6675. [PMID: 34899078 DOI: 10.1002/cpe.6675] [Reference Citation Analysis]
55 Cooney R, Wan AH, O'donncha F, Clifford E. Designing environmentally efficient aquafeeds through the use of multicriteria decision support tools. Current Opinion in Environmental Science & Health 2021;23:100276. [DOI: 10.1016/j.coesh.2021.100276] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
56 Bhutta ZA, Kanwal A, Ali M, Kulyar MF, Yao W, Shoaib M, Ashar A, Mahfooz A, Ijaz M, Ijaz N, Asif M, Nawaz S, Mahfooz MR, Kanwal T. Emerging nanotechnology role in the development of innovative solutions against COVID-19 pandemic. Nanotechnology 2021;32. [PMID: 34320471 DOI: 10.1088/1361-6528/ac189e] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
57 Antonarelli G, Corti C, Tarantino P, Ascione L, Cortes J, Romero P, Mittendorf EA, Disis ML, Curigliano G. Therapeutic cancer vaccines revamping: technology advancements and pitfalls. Ann Oncol 2021:S0923-7534(21)04457-4. [PMID: 34500046 DOI: 10.1016/j.annonc.2021.08.2153] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
58 Rawal K, Sinha R, Abbasi BA, Chaudhary A, Nath SK, Kumari P, Preeti P, Saraf D, Singh S, Mishra K, Gupta P, Mishra A, Sharma T, Gupta S, Singh P, Sood S, Subramani P, Dubey AK, Strych U, Hotez PJ, Bottazzi ME. Identification of vaccine targets in pathogens and design of a vaccine using computational approaches. Sci Rep 2021;11:17626. [PMID: 34475453 DOI: 10.1038/s41598-021-96863-x] [Cited by in F6Publishing: 7] [Reference Citation Analysis]
59 Aguiar VRC, Augusto DG, Castelli EC, Hollenbach JA, Meyer D, Nunes K, Petzl-Erler ML. An immunogenetic view of COVID-19. Genet Mol Biol 2021;44:e20210036. [PMID: 34436508 DOI: 10.1590/1678-4685-GMB-2021-0036] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
60 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: 1] [Cited by in F6Publishing: 11] [Article Influence: 1.0] [Reference Citation Analysis]
61 Ma J, Chen Y, Wu W, Chen Z. Structure and Function of N-Terminal Zinc Finger Domain of SARS-CoV-2 NSP2. Virol Sin 2021. [PMID: 34398430 DOI: 10.1007/s12250-021-00431-6] [Reference Citation Analysis]
62 Firouzi F, Farahani B, Daneshmand M, Grise K, Song J, Saracco R, Wang LL, Lo K, Angelov P, Soares E, Loh PS, Talebpour Z, Moradi R, Goodarzi M, Ashraf H, Talebpour M, Talebpour A, Romeo L, Das R, Heidari H, Pasquale D, Moody J, Woods C, Huang ES, Barnaghi P, Sarrafzadeh M, Li R, Beck KL, Isayev O, Sung N, Luo A. Harnessing the Power of Smart and Connected Health to Tackle COVID-19: IoT, AI, Robotics, and Blockchain for a Better World. IEEE Internet Things J 2021;8:12826-46. [PMID: 35782886 DOI: 10.1109/JIOT.2021.3073904] [Cited by in Crossref: 14] [Cited by in F6Publishing: 6] [Article Influence: 14.0] [Reference Citation Analysis]
63 Chadaga K, Prabhu S, Vivekananda BK, Niranjana S, Umakanth S, Pham DT. Battling COVID-19 using machine learning: A review. Cogent Engineering 2021;8:1958666. [DOI: 10.1080/23311916.2021.1958666] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
64 Gupta RM, Lall M. COVID-19 pandemic and artificial intelligence possibilities: A healthcare perspective. Med J Armed Forces India 2021;77:S242-4. [PMID: 34334887 DOI: 10.1016/j.mjafi.2021.06.001] [Reference Citation Analysis]
65 Wang Z, He Y. Precision omics data integration and analysis with interoperable ontologies and their application for COVID-19 research. Brief Funct Genomics 2021;20:235-48. [PMID: 34159360 DOI: 10.1093/bfgp/elab029] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
66 Alyasseri ZAA, Al-Betar MA, Doush IA, Awadallah MA, Abasi AK, Makhadmeh SN, Alomari OA, Abdulkareem KH, Adam A, Damasevicius R, Mohammed MA, Zitar RA. Review on COVID-19 diagnosis models based on machine learning and deep learning approaches. Expert Syst 2021;:e12759. [PMID: 34511689 DOI: 10.1111/exsy.12759] [Cited by in Crossref: 3] [Article Influence: 3.0] [Reference Citation Analysis]
67 Dong J, Wu H, Zhou D, Li K, Zhang Y, Ji H, Tong Z, Lou S, Liu Z. Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China. J Med Syst 2021;45:84. [PMID: 34302549 DOI: 10.1007/s10916-021-01757-0] [Reference Citation Analysis]
68 Bouchareb Y, Moradi Khaniabadi P, Al Kindi F, Al Dhuhli H, Shiri I, Zaidi H, Rahmim A. Artificial intelligence-driven assessment of radiological images for COVID-19. Comput Biol Med 2021;136:104665. [PMID: 34343890 DOI: 10.1016/j.compbiomed.2021.104665] [Reference Citation Analysis]
69 Barbieri D, Giuliani E, Del Prete A, Losi A, Villani M, Barbieri A. How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic. Int J Environ Res Public Health 2021;18:7648. [PMID: 34300099 DOI: 10.3390/ijerph18147648] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
70 Babcock S, Beverley J, Cowell LG, Smith B. The Infectious Disease Ontology in the age of COVID-19. J Biomed Semantics 2021;12:13. [PMID: 34275487 DOI: 10.1186/s13326-021-00245-1] [Cited by in F6Publishing: 4] [Reference Citation Analysis]
71 Ong E, Cooke MF, Huffman A, Xiang Z, Wong MU, Wang H, Seetharaman M, Valdez N, He Y. Vaxign2: the second generation of the first Web-based vaccine design program using reverse vaccinology and machine learning. Nucleic Acids Res 2021;49:W671-8. [PMID: 34009334 DOI: 10.1093/nar/gkab279] [Cited by in Crossref: 1] [Cited by in F6Publishing: 14] [Article Influence: 1.0] [Reference Citation Analysis]
72 Martínez-Flores D, Zepeda-Cervantes J, Cruz-Reséndiz A, Aguirre-Sampieri S, Sampieri A, Vaca L. SARS-CoV-2 Vaccines Based on the Spike Glycoprotein and Implications of New Viral Variants. Front Immunol 2021;12:701501. [PMID: 34322129 DOI: 10.3389/fimmu.2021.701501] [Cited by in Crossref: 3] [Cited by in F6Publishing: 39] [Article Influence: 3.0] [Reference Citation Analysis]
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