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For: Parimbelli E, Marini S, Sacchi L, Bellazzi R. Patient similarity for precision medicine: A systematic review. J Biomed Inform 2018;83:87-96. [PMID: 29864490 DOI: 10.1016/j.jbi.2018.06.001] [Cited by in Crossref: 39] [Cited by in F6Publishing: 26] [Article Influence: 9.8] [Reference Citation Analysis]
Number Citing Articles
1 Chen X, Garcelon N, Neuraz A, Billot K, Lelarge M, Bonald T, Garcia H, Martin Y, Benoit V, Vincent M, Faour H, Douillet M, Lyonnet S, Saunier S, Burgun A. Phenotypic similarity for rare disease: Ciliopathy diagnoses and subtyping. Journal of Biomedical Informatics 2019;100:103308. [DOI: 10.1016/j.jbi.2019.103308] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 2.7] [Reference Citation Analysis]
2 Skaf Y, Laubenbacher R. Topological Data Analysis in Biomedicine: A Review. Journal of Biomedical Informatics 2022. [DOI: 10.1016/j.jbi.2022.104082] [Reference Citation Analysis]
3 Hier DB, Brint SU. A Neuro-ontology for the neurological examination. BMC Med Inform Decis Mak 2020;20:47. [PMID: 32131804 DOI: 10.1186/s12911-020-1066-7] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
4 Coombes CE, Liu X, Abrams ZB, Coombes KR, Brock G. Simulation-derived best practices for clustering clinical data. J Biomed Inform 2021;118:103788. [PMID: 33862229 DOI: 10.1016/j.jbi.2021.103788] [Reference Citation Analysis]
5 Barchitta M, Maugeri A, Favara G, Riela PM, La Mastra C, La Rosa MC, San Lio RM, Gallo G, Mura I, Agodi A; SPIN-UTI Network. Cluster analysis identifies patients at risk of catheter-associated urinary tract infections in intensive care units: findings from the SPIN-UTI Network. J Hosp Infect 2021;107:57-63. [PMID: 33017617 DOI: 10.1016/j.jhin.2020.09.030] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 3.0] [Reference Citation Analysis]
6 Chang B, Choi Y, Jeon M, Lee J, Han KM, Kim A, Ham BJ, Kang J. ARPNet: Antidepressant Response Prediction Network for Major Depressive Disorder. Genes (Basel) 2019;10:E907. [PMID: 31703457 DOI: 10.3390/genes10110907] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 2.0] [Reference Citation Analysis]
7 Rodosthenous T, Shahrezaei V, Evangelou M. Integrating multi-OMICS data through sparse canonical correlation analysis for the prediction of complex traits: a comparison study. Bioinformatics 2020;36:4616-25. [PMID: 32437529 DOI: 10.1093/bioinformatics/btaa530] [Cited by in Crossref: 2] [Article Influence: 1.0] [Reference Citation Analysis]
8 Ng K, Kartoun U, Stavropoulos H, Zambrano JA, Tang PC. Personalized treatment options for chronic diseases using precision cohort analytics. Sci Rep 2021;11:1139. [PMID: 33441956 DOI: 10.1038/s41598-021-80967-5] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
9 Wang N, Huang Y, Liu H, Zhang Z, Wei L, Fei X, Chen H. Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records. BMC Med Inform Decis Mak 2021;21:58. [PMID: 34330261 DOI: 10.1186/s12911-021-01432-x] [Reference Citation Analysis]
10 Hier DB, Kopel J, Brint SU, Wunsch DC 2nd, Olbricht GR, Azizi S, Allen B. Evaluation of standard and semantically-augmented distance metrics for neurology patients. BMC Med Inform Decis Mak 2020;20:203. [PMID: 32843023 DOI: 10.1186/s12911-020-01217-8] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
11 Greenbury SF, Ougham K, Wu J, Battersby C, Gale C, Modi N, Angelini ED. Identification of variation in nutritional practice in neonatal units in England and association with clinical outcomes using agnostic machine learning. Sci Rep 2021;11:7178. [PMID: 33785776 DOI: 10.1038/s41598-021-85878-z] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
12 Fang HSA, Tan NC, Tan WY, Oei RW, Lee ML, Hsu W. Patient similarity analytics for explainable clinical risk prediction. BMC Med Inform Decis Mak 2021;21:207. [PMID: 34210320 DOI: 10.1186/s12911-021-01566-y] [Reference Citation Analysis]
13 Cho JS, Shrestha S, Kagiyama N, Hu L, Ghaffar YA, Casaclang-Verzosa G, Zeb I, Sengupta PP. A Network-Based "Phenomics" Approach for Discovering Patient Subtypes From High-Throughput Cardiac Imaging Data. JACC Cardiovasc Imaging 2020;13:1655-70. [PMID: 32762883 DOI: 10.1016/j.jcmg.2020.02.008] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 3.5] [Reference Citation Analysis]
14 Serrap A, Saarimäki LA, Pavel A, Giudice GD, Fratello M, Cattelani L, Federico A, Laurino O, Marwah VS, Fortino V, Scala G, Sofia Kinaret PA, Greco D. Nextcast: a software suite to analyse and model toxicogenomics data. Computational and Structural Biotechnology Journal 2022. [DOI: 10.1016/j.csbj.2022.03.014] [Reference Citation Analysis]
15 Buyer J, Oeser A, Grieb N, Dietz A, Neumuth T, Stoehr M. Decision Support for Oropharyngeal Cancer Patients Based on Data-Driven Similarity Metrics for Medical Case Comparison. Diagnostics 2022;12:999. [DOI: 10.3390/diagnostics12040999] [Reference Citation Analysis]
16 Boniolo G, Campaner R, Carrara M. Patient Similarity in the Era of Precision Medicine: A Philosophical Analysis. Erkenn. [DOI: 10.1007/s10670-021-00483-w] [Reference Citation Analysis]
17 Gallo J, Kriegova E, Kudelka M, Lostak J, Radvansky M. Gender Differences in Contribution of Smoking, Low Physical Activity, and High BMI to Increased Risk of Early Reoperation After TKA. J Arthroplasty 2020;35:1545-57. [PMID: 32067896 DOI: 10.1016/j.arth.2020.01.056] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
18 Doll JA, Nelson AJ, Kaltenbach LA, Wojdyla D, Waldo SW, Rao SV, Wang TY. Percutaneous Coronary Intervention Operator Profiles and Associations With In-Hospital Mortality. Circ Cardiovasc Interv 2021;:CIRCINTERVENTIONS121010909. [PMID: 34847693 DOI: 10.1161/CIRCINTERVENTIONS.121.010909] [Reference Citation Analysis]
19 Ferro S, Bottigliengo D, Gregori D, Fabricio ASC, Gion M, Baldi I. Phenomapping of Patients with Primary Breast Cancer Using Machine Learning-Based Unsupervised Cluster Analysis. J Pers Med 2021;11:272. [PMID: 33916398 DOI: 10.3390/jpm11040272] [Reference Citation Analysis]
20 Lo Bue E, Scalia G, Nicoletti GF, Maugeri R, Iacopino DG, Zabbia G, Umana GE, Graziano F. The Boundless World of Cranioplasty: A Multicenter Retrospective Study and Therapeutic Flow-Chart Patient-Specific Based. J Craniofac Surg 2021;32:2758-62. [PMID: 34727474 DOI: 10.1097/SCS.0000000000007903] [Reference Citation Analysis]
21 Seligson ND, Warner JL, Dalton WS, Martin D, Miller RS, Patt D, Kehl KL, Palchuk MB, Alterovitz G, Wiley LK, Huang M, Shen F, Wang Y, Nguyen KA, Wong AF, Meric-Bernstam F, Bernstam EV, Chen JL. Recommendations for patient similarity classes: results of the AMIA 2019 workshop on defining patient similarity. J Am Med Inform Assoc 2020;27:1808-12. [PMID: 32885823 DOI: 10.1093/jamia/ocaa159] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 5.0] [Reference Citation Analysis]
22 Saxena A, Paredes-Echeverri S, Michaelis R, Popkirov S, Perez DL. Using the Biopsychosocial Model to Guide Patient-Centered Neurological Treatments. Semin Neurol 2022. [PMID: 35114695 DOI: 10.1055/s-0041-1742145] [Reference Citation Analysis]
23 Kim Y, Kim J. Identification of New Clusters from Labeled Data Using Mixture Models. J Comput Biol 2022. [PMID: 35384743 DOI: 10.1089/cmb.2021.0443] [Reference Citation Analysis]
24 Gu Y, Yang X, Tian L, Yang H, Lv J, Yang C, Wang J, Xi J, Kong G, Zhang W. Structure-Aware Siamese Graph Neural Networks for Encounter-Level Patient Similarity Learning. J Biomed Inform 2022;:104027. [PMID: 35181493 DOI: 10.1016/j.jbi.2022.104027] [Reference Citation Analysis]
25 Combi C, Pozzi G. Clinical Information Systems and Artificial Intelligence: Recent Research Trends. Yearb Med Inform 2019;28:83-94. [PMID: 31419820 DOI: 10.1055/s-0039-1677915] [Cited by in Crossref: 8] [Cited by in F6Publishing: 4] [Article Influence: 2.7] [Reference Citation Analysis]
26 Wang N, Huang Y, Liu H, Fei X, Wei L, Zhao X, Chen H. Measurement and application of patient similarity in personalized predictive modeling based on electronic medical records. Biomed Eng Online 2019;18:98. [PMID: 31601207 DOI: 10.1186/s12938-019-0718-2] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 1.3] [Reference Citation Analysis]
27 Nicora G, Moretti F, Sauta E, Della Porta M, Malcovati L, Cazzola M, Quaglini S, Bellazzi R. A continuous-time Markov model approach for modeling myelodysplastic syndromes progression from cross-sectional data. J Biomed Inform 2020;104:103398. [PMID: 32113003 DOI: 10.1016/j.jbi.2020.103398] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
28 Huang M, Shah ND, Yao L. Evaluating global and local sequence alignment methods for comparing patient medical records. BMC Med Inform Decis Mak 2019;19:263. [PMID: 31856819 DOI: 10.1186/s12911-019-0965-y] [Cited by in Crossref: 5] [Cited by in F6Publishing: 1] [Article Influence: 1.7] [Reference Citation Analysis]
29 Torres-Espín A, Haefeli J, Ehsanian R, Torres D, Almeida CA, Huie JR, Chou A, Morozov D, Sanderson N, Dirlikov B, Suen CG, Nielson JL, Kyritsis N, Hemmerle DD, Talbott JF, Manley GT, Dhall SS, Whetstone WD, Bresnahan JC, Beattie MS, McKenna SL, Pan JZ, Ferguson AR; TRACK-SCI Investigators. Topological network analysis of patient similarity for precision management of acute blood pressure in spinal cord injury. Elife 2021;10:e68015. [PMID: 34783309 DOI: 10.7554/eLife.68015] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
30 McDowell L, Casswell G, Bressel M, Drosdowsky A, Rischin D, Coleman A, Shrestha S, D'Costa I, Fua T, Tiong A, Liu C, Gough K. Symptom burden, quality of life, functioning and emotional distress in survivors of human papillomavirus associated oropharyngeal cancer: An Australian cohort. Oral Oncol 2021;122:105560. [PMID: 34653749 DOI: 10.1016/j.oraloncology.2021.105560] [Reference Citation Analysis]
31 Tokodi M, Shrestha S, Bianco C, Kagiyama N, Casaclang-Verzosa G, Narula J, Sengupta PP. Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine. JACC Cardiovasc Imaging 2020;13:1119-32. [PMID: 32199835 DOI: 10.1016/j.jcmg.2019.12.018] [Cited by in Crossref: 10] [Cited by in F6Publishing: 12] [Article Influence: 5.0] [Reference Citation Analysis]
32 Ryan JC, Viana JN, Sellak H, Gondalia S, O'Callaghan N. Defining precision health: a scoping review protocol. BMJ Open 2021;11:e044663. [PMID: 33593787 DOI: 10.1136/bmjopen-2020-044663] [Reference Citation Analysis]
33 Pranata S, Wu SV, Alizargar J, Liu JH, Liang SY, Lu YY. Precision Health Care Elements, Definitions, and Strategies for Patients with Diabetes: A Literature Review. Int J Environ Res Public Health 2021;18:6535. [PMID: 34204428 DOI: 10.3390/ijerph18126535] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
34 Afsharnejad B, Falkmer M, Black MH, Alach T, Lenhard F, Fridell A, Coco C, Milne K, Bölte S, Girdler S. KONTAKT® social skills group training for Australian adolescents with autism spectrum disorder: a randomized controlled trial. Eur Child Adolesc Psychiatry 2021. [PMID: 34052908 DOI: 10.1007/s00787-021-01814-6] [Reference Citation Analysis]
35 Denicolai S, Previtali P. Precision Medicine: Implications for value chains and business models in life sciences. Technological Forecasting and Social Change 2020;151:119767. [DOI: 10.1016/j.techfore.2019.119767] [Cited by in Crossref: 12] [Cited by in F6Publishing: 2] [Article Influence: 6.0] [Reference Citation Analysis]
36 Menon U, Cohn E, Downs CA, Gephart SM, Redwine L. Precision health research and implementation reviewed through the conNECT framework. Nurs Outlook 2019;67:302-10. [PMID: 31280842 DOI: 10.1016/j.outlook.2019.05.010] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
37 Jia Z, Zeng X, Duan H, Lu X, Li H. A patient-similarity-based model for diagnostic prediction. Int J Med Inform 2020;135:104073. [PMID: 31923816 DOI: 10.1016/j.ijmedinf.2019.104073] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
38 Jorm LR. Commentary: Towards machine learning-enabled epidemiology. Int J Epidemiol 2021;49:1770-3. [PMID: 33485274 DOI: 10.1093/ije/dyaa242] [Reference Citation Analysis]
39 Torres Moral T, Sanchez-niubo A, Monistrol-mula A, Gerardi C, Banzi R, Garcia P, Demotes-mainard J, Haro J; the PERMIT Group. Methods for Stratification and Validation Cohorts: A Scoping Review. JPM 2022;12:688. [DOI: 10.3390/jpm12050688] [Reference Citation Analysis]
40 Dagliati A, Gatta R, Malovini A, Tibollo V, Sacchi L, Cascini F, Chiovato L, Bellazzi R. A Process Mining Pipeline to Characterize COVID-19 Patients' Trajectories and Identify Relevant Temporal Phenotypes From EHR Data. Front Public Health 2022;10:815674. [DOI: 10.3389/fpubh.2022.815674] [Reference Citation Analysis]
41 Wang N, Wang M, Zhou Y, Liu H, Wei L, Fei X, Chen H. Sequential Data-Based Patient Similarity Framework for Patient Outcome Prediction: Algorithm Development. J Med Internet Res 2022;24:e30720. [PMID: 34989682 DOI: 10.2196/30720] [Reference Citation Analysis]
42 Parimbelli E, Wilk S, Cornet R, Sniatala P, Sniatala K, Glaser SLC, Fraterman I, Boekhout AH, Ottaviano M, Peleg M. A review of AI and Data Science support for cancer management. Artif Intell Med 2021;117:102111. [PMID: 34127240 DOI: 10.1016/j.artmed.2021.102111] [Reference Citation Analysis]