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For: Saez-Rodriguez J, Costello JC, Friend SH, Kellen MR, Mangravite L, Meyer P, Norman T, Stolovitzky G. Crowdsourcing biomedical research: leveraging communities as innovation engines. Nat Rev Genet 2016;17:470-86. [PMID: 27418159 DOI: 10.1038/nrg.2016.69] [Cited by in Crossref: 107] [Cited by in F6Publishing: 73] [Article Influence: 21.4] [Reference Citation Analysis]
Number Citing Articles
1 Banda JM, Tekumalla R, Wang G, Yu J, Liu T, Ding Y, Artemova E, Tutubalina E, Chowell G. A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research—An International Collaboration. Epidemiologia 2021;2:315-24. [DOI: 10.3390/epidemiologia2030024] [Cited by in Crossref: 11] [Cited by in F6Publishing: 2] [Article Influence: 11.0] [Reference Citation Analysis]
2 Gilvary C, Madhukar N, Elkhader J, Elemento O. The Missing Pieces of Artificial Intelligence in Medicine. Trends in Pharmacological Sciences 2019;40:555-64. [DOI: 10.1016/j.tips.2019.06.001] [Cited by in Crossref: 17] [Cited by in F6Publishing: 11] [Article Influence: 5.7] [Reference Citation Analysis]
3 Boué S, Exner T, Ghosh S, Belcastro V, Dokler J, Page D, Boda A, Bonjour F, Hardy B, Vanscheeuwijck P, Hoeng J, Peitsch M. Supporting evidence-based analysis for modified risk tobacco products through a toxicology data-sharing infrastructure. F1000Res 2017;6:12. [PMID: 29123642 DOI: 10.12688/f1000research.10493.2] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 1.4] [Reference Citation Analysis]
4 Lu H, Xu H, Zhao J, Hou D. A Deep Ultraviolet Mode-locked Laser Based on a Neural Network. Sci Rep 2020;10:116. [PMID: 31924824 DOI: 10.1038/s41598-019-56845-6] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
5 Schaffter T, Buist DSM, Lee CI, Nikulin Y, Ribli D, Guan Y, Lotter W, Jie Z, Du H, Wang S, Feng J, Feng M, Kim HE, Albiol F, Albiol A, Morrell S, Wojna Z, Ahsen ME, Asif U, Jimeno Yepes A, Yohanandan S, Rabinovici-Cohen S, Yi D, Hoff B, Yu T, Chaibub Neto E, Rubin DL, Lindholm P, Margolies LR, McBride RB, Rothstein JH, Sieh W, Ben-Ari R, Harrer S, Trister A, Friend S, Norman T, Sahiner B, Strand F, Guinney J, Stolovitzky G, Mackey L, Cahoon J, Shen L, Sohn JH, Trivedi H, Shen Y, Buturovic L, Pereira JC, Cardoso JS, Castro E, Kalleberg KT, Pelka O, Nedjar I, Geras KJ, Nensa F, Goan E, Koitka S, Caballero L, Cox DD, Krishnaswamy P, Pandey G, Friedrich CM, Perrin D, Fookes C, Shi B, Cardoso Negrie G, Kawczynski M, Cho K, Khoo CS, Lo JY, Sorensen AG, Jung H; and the DM DREAM Consortium. Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms. JAMA Netw Open 2020;3:e200265. [PMID: 32119094 DOI: 10.1001/jamanetworkopen.2020.0265] [Cited by in Crossref: 58] [Cited by in F6Publishing: 46] [Article Influence: 29.0] [Reference Citation Analysis]
6 Ali M, Aittokallio T. Machine learning and feature selection for drug response prediction in precision oncology applications. Biophys Rev 2019;11:31-9. [PMID: 30097794 DOI: 10.1007/s12551-018-0446-z] [Cited by in Crossref: 71] [Cited by in F6Publishing: 52] [Article Influence: 17.8] [Reference Citation Analysis]
7 Correa da Rosa J, Kim J, Tian S, Tomalin LE, Krueger JG, Suárez-Fariñas M. Shrinking the Psoriasis Assessment Gap: Early Gene-Expression Profiling Accurately Predicts Response to Long-Term Treatment. J Invest Dermatol 2017;137:305-12. [PMID: 27667537 DOI: 10.1016/j.jid.2016.09.015] [Cited by in Crossref: 29] [Cited by in F6Publishing: 23] [Article Influence: 4.8] [Reference Citation Analysis]
8 Maier-Hein L, Reinke A, Kozubek M, Martel AL, Arbel T, Eisenmann M, Hanbury A, Jannin P, Müller H, Onogur S, Saez-Rodriguez J, van Ginneken B, Kopp-Schneider A, Landman BA. BIAS: Transparent reporting of biomedical image analysis challenges. Med Image Anal 2020;66:101796. [PMID: 32911207 DOI: 10.1016/j.media.2020.101796] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
9 Tarca AL, Gong X, Romero R, Yang W, Duan Z, Yang H, Zhang C, Wang P. Human blood gene signature as a marker for smoking exposure: computational approaches of the top ranked teams in the sbv IMPROVER Systems Toxicology challenge. Comput Toxicol 2018;5:31-7. [PMID: 29556588 DOI: 10.1016/j.comtox.2017.07.003] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 0.6] [Reference Citation Analysis]
10 Ballouz S, Dobin A, Gingeras TR, Gillis J. The fractured landscape of RNA-seq alignment: the default in our STARs. Nucleic Acids Res 2018;46:5125-38. [PMID: 29718481 DOI: 10.1093/nar/gky325] [Cited by in Crossref: 12] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
11 Goecks J, Jalili V, Heiser LM, Gray JW. How Machine Learning Will Transform Biomedicine. Cell 2020;181:92-101. [PMID: 32243801 DOI: 10.1016/j.cell.2020.03.022] [Cited by in Crossref: 46] [Cited by in F6Publishing: 32] [Article Influence: 23.0] [Reference Citation Analysis]
12 Vermicelli S, Cricelli L, Grimaldi M. How can crowdsourcing help tackle the COVID‐19 pandemic? An explorative overview of innovative collaborative practices. R&D Management 2021;51:183-94. [DOI: 10.1111/radm.12443] [Cited by in Crossref: 12] [Cited by in F6Publishing: 5] [Article Influence: 6.0] [Reference Citation Analysis]
13 Vangay P, Burgin J, Johnston A, Beck KL, Berrios DC, Blumberg K, Canon S, Chain P, Chandonia JM, Christianson D, Costes SV, Damerow J, Duncan WD, Dundore-Arias JP, Fagnan K, Galazka JM, Gibbons SM, Hays D, Hervey J, Hu B, Hurwitz BL, Jaiswal P, Joachimiak MP, Kinkel L, Ladau J, Martin SL, McCue LA, Miller K, Mouncey N, Mungall C, Pafilis E, Reddy TBK, Richardson L, Roux S, Schriml LM, Shaffer JP, Sundaramurthi JC, Thompson LR, Timme RE, Zheng J, Wood-Charlson EM, Eloe-Fadrosh EA. Microbiome Metadata Standards: Report of the National Microbiome Data Collaborative's Workshop and Follow-On Activities. mSystems 2021;6:e01194-20. [PMID: 33622857 DOI: 10.1128/mSystems.01194-20] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
14 Huang C, Mezencev R, McDonald JF, Vannberg F. Open source machine-learning algorithms for the prediction of optimal cancer drug therapies. PLoS One 2017;12:e0186906. [PMID: 29073279 DOI: 10.1371/journal.pone.0186906] [Cited by in Crossref: 43] [Cited by in F6Publishing: 33] [Article Influence: 8.6] [Reference Citation Analysis]
15 Davis S, Button-Simons K, Bensellak T, Ahsen EM, Checkley L, Foster GJ, Su X, Moussa A, Mapiye D, Khoo SK, Nosten F, Anderson TJC, Vendrely K, Bletz J, Yu T, Panji S, Ghouila A, Mulder N, Norman T, Kern S, Meyer P, Stolovitzky G, Ferdig MT, Siwo GH. Leveraging crowdsourcing to accelerate global health solutions. Nat Biotechnol 2019;37:848-50. [PMID: 31324891 DOI: 10.1038/s41587-019-0180-5] [Cited by in Crossref: 17] [Cited by in F6Publishing: 4] [Article Influence: 5.7] [Reference Citation Analysis]
16 Chen JC, Christiano AM. Out of Many, One: Computational Reconstruction of Mouse Skin using Single-Cell Transcriptomics. Cell Stem Cell 2016;19:421-2. [PMID: 27716520 DOI: 10.1016/j.stem.2016.09.009] [Reference Citation Analysis]
17 Chandonia JM, Adhikari A, Carraro M, Chhibber A, Cutting GR, Fu Y, Gasparini A, Jones DT, Kramer A, Kundu K, Lam HYK, Leonardi E, Moult J, Pal LR, Searls DB, Shah S, Sunyaev S, Tosatto SCE, Yin Y, Buckley BA. Lessons from the CAGI-4 Hopkins clinical panel challenge. Hum Mutat 2017;38:1155-68. [PMID: 28397312 DOI: 10.1002/humu.23225] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.6] [Reference Citation Analysis]
18 Seaby EG, Ennis S. Challenges in the diagnosis and discovery of rare genetic disorders using contemporary sequencing technologies. Brief Funct Genomics 2020;19:243-58. [PMID: 32393978 DOI: 10.1093/bfgp/elaa009] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
19 Menden MP, Wang D, Mason MJ, Szalai B, Bulusu KC, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang IS, Ghazoui Z, Ahsen ME, Vogel R, Neto EC, Norman T, Tang EKY, Garnett MJ, Veroli GYD, Fawell S, Stolovitzky G, Guinney J, Dry JR, Saez-Rodriguez J; AstraZeneca-Sanger Drug Combination DREAM Consortium. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen. Nat Commun 2019;10:2674. [PMID: 31209238 DOI: 10.1038/s41467-019-09799-2] [Cited by in Crossref: 106] [Cited by in F6Publishing: 74] [Article Influence: 35.3] [Reference Citation Analysis]
20 Tucker JD, Day S, Tang W, Bayus B. Crowdsourcing in medical research: concepts and applications. PeerJ 2019;7:e6762. [PMID: 30997295 DOI: 10.7717/peerj.6762] [Cited by in Crossref: 43] [Cited by in F6Publishing: 36] [Article Influence: 14.3] [Reference Citation Analysis]
21 Mohr SE, Tattikota SG, Xu J, Zirin J, Hu Y, Perrimon N. Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila. Genetics 2021;217:iyab019. [PMID: 33713129 DOI: 10.1093/genetics/iyab019] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
22 Aktı Ş, Kamar D, Özlü ÖA, Soydemir I, Akcan M, Kul A, Rekik I. A comparative study of machine learning methods for predicting the evolution of brain connectivity from a baseline timepoint. J Neurosci Methods 2022;368:109475. [PMID: 34995648 DOI: 10.1016/j.jneumeth.2022.109475] [Reference Citation Analysis]
23 Das R, Keep B, Washington P, Riedel-Kruse IH. Scientific Discovery Games for Biomedical Research. Annu Rev Biomed Data Sci 2019;2:253-79. [PMID: 34308269 DOI: 10.1146/annurev-biodatasci-072018-021139] [Cited by in Crossref: 4] [Article Influence: 1.3] [Reference Citation Analysis]
24 Bülow RD, Dimitrov D, Boor P, Saez-Rodriguez J. How will artificial intelligence and bioinformatics change our understanding of IgA Nephropathy in the next decade? Semin Immunopathol 2021. [PMID: 33835214 DOI: 10.1007/s00281-021-00847-y] [Reference Citation Analysis]
25 [DOI: 10.1101/181677] [Cited by in Crossref: 10] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
26 Wells DK, van Buuren MM, Dang KK, Hubbard-Lucey VM, Sheehan KCF, Campbell KM, Lamb A, Ward JP, Sidney J, Blazquez AB, Rech AJ, Zaretsky JM, Comin-Anduix B, Ng AHC, Chour W, Yu TV, Rizvi H, Chen JM, Manning P, Steiner GM, Doan XC, Merghoub T, Guinney J, Kolom A, Selinsky C, Ribas A, Hellmann MD, Hacohen N, Sette A, Heath JR, Bhardwaj N, Ramsdell F, Schreiber RD, Schumacher TN, Kvistborg P, Defranoux NA; Tumor Neoantigen Selection Alliance. Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction. Cell 2020;183:818-834.e13. [PMID: 33038342 DOI: 10.1016/j.cell.2020.09.015] [Cited by in Crossref: 52] [Cited by in F6Publishing: 49] [Article Influence: 26.0] [Reference Citation Analysis]
27 Zhang Y, Lin H, Yang Z, Wang J, Sun Y, Xu B, Zhao Z. Neural network-based approaches for biomedical relation classification: A review. Journal of Biomedical Informatics 2019;99:103294. [DOI: 10.1016/j.jbi.2019.103294] [Cited by in Crossref: 15] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
28 Li H, Panwar B, Omenn GS, Guan Y. Accurate prediction of personalized olfactory perception from large-scale chemoinformatic features. Gigascience 2018;7. [PMID: 29267859 DOI: 10.1093/gigascience/gix127] [Cited by in Crossref: 17] [Cited by in F6Publishing: 13] [Article Influence: 4.3] [Reference Citation Analysis]
29 González P, Argüeso-alejandro P, Penas DR, Pardo XC, Saez-rodriguez J, Banga JR, Doallo R. Hybrid parallel multimethod hyperheuristic for mixed-integer dynamic optimization problems in computational systems biology. J Supercomput 2019;75:3471-98. [DOI: 10.1007/s11227-019-02871-0] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
30 Guinney J, Wang T, Laajala TD, Winner KK, Bare JC, Neto EC, Khan SA, Peddinti G, Airola A, Pahikkala T, Mirtti T, Yu T, Bot BM, Shen L, Abdallah K, Norman T, Friend S, Stolovitzky G, Soule H, Sweeney CJ, Ryan CJ, Scher HI, Sartor O, Xie Y, Aittokallio T, Zhou FL, Costello JC; Prostate Cancer Challenge DREAM Community. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data. Lancet Oncol 2017;18:132-42. [PMID: 27864015 DOI: 10.1016/S1470-2045(16)30560-5] [Cited by in Crossref: 74] [Cited by in F6Publishing: 45] [Article Influence: 12.3] [Reference Citation Analysis]
31 Sparks R, Lau WW, Tsang JS. Expanding the Immunology Toolbox: Embracing Public-Data Reuse and Crowdsourcing. Immunity 2016;45:1191-204. [DOI: 10.1016/j.immuni.2016.12.008] [Cited by in Crossref: 12] [Cited by in F6Publishing: 11] [Article Influence: 2.0] [Reference Citation Analysis]
32 Tanevski J, Nguyen T, Truong B, Karaiskos N, Ahsen ME, Zhang X, Shu C, Xu K, Liang X, Hu Y, Pham HV, Xiaomei L, Le TD, Tarca AL, Bhatti G, Romero R, Karathanasis N, Loher P, Chen Y, Ouyang Z, Mao D, Zhang Y, Zand M, Ruan J, Hafemeister C, Qiu P, Tran D, Nguyen T, Gabor A, Yu T, Guinney J, Glaab E, Krause R, Banda P, Stolovitzky G, Rajewsky N, Saez-Rodriguez J, Meyer P; DREAM SCTC Consortium. Gene selection for optimal prediction of cell position in tissues from single-cell transcriptomics data. Life Sci Alliance 2020;3:e202000867. [PMID: 32972997 DOI: 10.26508/lsa.202000867] [Cited by in Crossref: 10] [Cited by in F6Publishing: 6] [Article Influence: 5.0] [Reference Citation Analysis]
33 Lau WW, Sparks R, Tsang JS; OMiCC Jamboree Working Group. Meta-analysis of crowdsourced data compendia suggests pan-disease transcriptional signatures of autoimmunity. F1000Res 2016;5:2884. [PMID: 28491277 DOI: 10.12688/f1000research.10465.1] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
34 Uhlmann EL, Ebersole CR, Chartier CR, Errington TM, Kidwell MC, Lai CK, McCarthy RJ, Riegelman A, Silberzahn R, Nosek BA. Scientific Utopia III: Crowdsourcing Science. Perspect Psychol Sci 2019;14:711-33. [PMID: 31260639 DOI: 10.1177/1745691619850561] [Cited by in Crossref: 26] [Cited by in F6Publishing: 8] [Article Influence: 8.7] [Reference Citation Analysis]
35 Tarca AL, Pataki BÁ, Romero R, Sirota M, Guan Y, Kutum R, Gomez-Lopez N, Done B, Bhatti G, Yu T, Andreoletti G, Chaiworapongsa T, Hassan SS, Hsu CD, Aghaeepour N, Stolovitzky G, Csabai I, Costello JC; DREAM Preterm Birth Prediction Challenge Consortium. Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth. Cell Rep Med 2021;2:100323. [PMID: 34195686 DOI: 10.1016/j.xcrm.2021.100323] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
36 Soon JM, Saguy IS. Crowdsourcing: A new conceptual view for food safety and quality. Trends in Food Science & Technology 2017;66:63-72. [DOI: 10.1016/j.tifs.2017.05.013] [Cited by in Crossref: 10] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
37 Camacho DM, Collins KM, Powers RK, Costello JC, Collins JJ. Next-Generation Machine Learning for Biological Networks. Cell. 2018;173:1581-1592. [PMID: 29887378 DOI: 10.1016/j.cell.2018.05.015] [Cited by in Crossref: 317] [Cited by in F6Publishing: 234] [Article Influence: 79.3] [Reference Citation Analysis]
38 Stumpf MPH. Multi-model and network inference based on ensemble estimates: avoiding the madness of crowds. J R Soc Interface 2020;17:20200419. [PMID: 33081645 DOI: 10.1098/rsif.2020.0419] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
39 Fitzpatrick R, Stefan MI. Validation Through Collaboration: Encouraging Team Efforts to Ensure Internal and External Validity of Computational Models of Biochemical Pathways. Neuroinformatics 2022. [PMID: 35543917 DOI: 10.1007/s12021-022-09584-5] [Reference Citation Analysis]
40 Ellrott K, Buchanan A, Creason A, Mason M, Schaffter T, Hoff B, Eddy J, Chilton JM, Yu T, Stuart JM, Saez-Rodriguez J, Stolovitzky G, Boutros PC, Guinney J. Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges. Genome Biol 2019;20:195. [PMID: 31506093 DOI: 10.1186/s13059-019-1794-0] [Cited by in Crossref: 10] [Cited by in F6Publishing: 9] [Article Influence: 3.3] [Reference Citation Analysis]
41 Gabor A, Tognetti M, Driessen A, Tanevski J, Guo B, Cao W, Shen H, Yu T, Chung V, Bodenmiller B, Saez-Rodriguez J; Single Cell Signaling in Breast Cancer DREAM Consortium members. Cell-to-cell and type-to-type heterogeneity of signaling networks: insights from the crowd. Mol Syst Biol 2021;17:e10402. [PMID: 34661974 DOI: 10.15252/msb.202110402] [Reference Citation Analysis]
42 Capriotti E, Martelli PL, Fariselli P, Casadio R. Blind prediction of deleterious amino acid variations with SNPs&GO. Hum Mutat 2017;38:1064-71. [PMID: 28102005 DOI: 10.1002/humu.23179] [Cited by in Crossref: 9] [Cited by in F6Publishing: 3] [Article Influence: 1.8] [Reference Citation Analysis]
43 Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, Bermejo-Martin JF, Almansa R, Tamayo E, Davenport EE, Burnham KL, Hinds CJ, Knight JC, Woods CW, Kingsmore SF, Ginsburg GS, Wong HR, Parnell GP, Tang B, Moldawer LL, Moore FE, Omberg L, Khatri P, Tsalik EL, Mangravite LM, Langley RJ. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun 2018;9:694. [PMID: 29449546 DOI: 10.1038/s41467-018-03078-2] [Cited by in Crossref: 92] [Cited by in F6Publishing: 81] [Article Influence: 23.0] [Reference Citation Analysis]
44 Wasik S, Antczak M, Badura J, Laskowski A, Sternal T. A Survey on Online Judge Systems and Their Applications. ACM Comput Surv 2019;51:1-34. [DOI: 10.1145/3143560] [Cited by in Crossref: 57] [Cited by in F6Publishing: 8] [Article Influence: 19.0] [Reference Citation Analysis]
45 Douglass EF Jr, Allaway RJ, Szalai B, Wang W, Tian T, Fernández-Torras A, Realubit R, Karan C, Zheng S, Pessia A, Tanoli Z, Jafari M, Wan F, Li S, Xiong Y, Duran-Frigola M, Bertoni M, Badia-I-Mompel P, Mateo L, Guitart-Pla O, Chung V, Tang J, Zeng J, Aloy P, Saez-Rodriguez J, Guinney J, Gerhard DS, Califano A; DREAM CTD-squared Pancancer Drug Activity Challenge Consortium. A community challenge for a pancancer drug mechanism of action inference from perturbational profile data. Cell Rep Med 2022;3:100492. [PMID: 35106508 DOI: 10.1016/j.xcrm.2021.100492] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
46 Thompson DC, Bentzien J. Crowdsourcing and open innovation in drug discovery: recent contributions and future directions. Drug Discov Today 2020;25:2284-93. [PMID: 33011343 DOI: 10.1016/j.drudis.2020.09.020] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
47 Liu C, Ma Y, Zhao J, Nussinov R, Zhang Y, Cheng F, Zhang Z. Computational network biology: Data, models, and applications. Physics Reports 2020;846:1-66. [DOI: 10.1016/j.physrep.2019.12.004] [Cited by in Crossref: 32] [Cited by in F6Publishing: 6] [Article Influence: 16.0] [Reference Citation Analysis]
48 Korcsmaros T, Schneider MV, Superti-Furga G. Next generation of network medicine: interdisciplinary signaling approaches. Integr Biol (Camb) 2017;9:97-108. [PMID: 28106223 DOI: 10.1039/c6ib00215c] [Cited by in Crossref: 20] [Cited by in F6Publishing: 16] [Article Influence: 4.0] [Reference Citation Analysis]
49 Bergquist T, Yan Y, Schaffter T, Yu T, Pejaver V, Hammarlund N, Prosser J, Guinney J, Mooney S. Piloting a model-to-data approach to enable predictive analytics in health care through patient mortality prediction. J Am Med Inform Assoc 2020;27:1393-400. [PMID: 32638010 DOI: 10.1093/jamia/ocaa083] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
50 Cagan R, Meyer P. Rethinking cancer: current challenges and opportunities in cancer research. Dis Model Mech 2017;10:349-52. [PMID: 28381596 DOI: 10.1242/dmm.030007] [Cited by in Crossref: 23] [Cited by in F6Publishing: 17] [Article Influence: 4.6] [Reference Citation Analysis]
51 Cohain A, Divaraniya AA, Zhu K, Scarpa JR, Kasarskis A, Zhu J, Chang R, Dudley JT, Schadt EE. EXPLORING THE REPRODUCIBILITY OF PROBABILISTIC CAUSAL MOLECULAR NETWORK MODELS. Pac Symp Biocomput 2017;22:120-31. [PMID: 27896968 DOI: 10.1142/9789813207813_0013] [Cited by in F6Publishing: 9] [Reference Citation Analysis]
52 Manco L, Maffei N, Strolin S, Vichi S, Bottazzi L, Strigari L. Basic of machine learning and deep learning in imaging for medical physicists. Physica Medica 2021;83:194-205. [DOI: 10.1016/j.ejmp.2021.03.026] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
53 Créquit P, Mansouri G, Benchoufi M, Vivot A, Ravaud P. Mapping of Crowdsourcing in Health: Systematic Review. J Med Internet Res 2018;20:e187. [PMID: 29764795 DOI: 10.2196/jmir.9330] [Cited by in Crossref: 35] [Cited by in F6Publishing: 37] [Article Influence: 8.8] [Reference Citation Analysis]
54 Blasco A, Endres MG, Sergeev RA, Jonchhe A, Macaluso NJM, Narayan R, Natoli T, Paik JH, Briney B, Wu C, Su AI, Subramanian A, Lakhani KR. Advancing computational biology and bioinformatics research through open innovation competitions. PLoS One 2019;14:e0222165. [PMID: 31560691 DOI: 10.1371/journal.pone.0222165] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
55 Ulahannan JP, Narayanan N, Thalhath N, Prabhakaran P, Chaliyeduth S, Suresh SP, Mohammed M, Rajeevan E, Joseph S, Balakrishnan A, Uthaman J, Karingamadathil M, Thomas ST, Sureshkumar U, Balan S, Vellichirammal NN; Collective for Open Data Distribution-Keralam (CODD-K) consortium. A citizen science initiative for open data and visualization of COVID-19 outbreak in Kerala, India. J Am Med Inform Assoc 2020;27:1913-20. [PMID: 32761211 DOI: 10.1093/jamia/ocaa203] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
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