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dc.contributor.authorSohail, Ayesha
dc.contributor.authorYounas, Muhammad
dc.contributor.authorBhatti, Yousaf
dc.contributor.authorLi, Zhiwu
dc.contributor.authorTunç, Sümeyye
dc.contributor.authorAbid, Muhammad
dc.date.accessioned10.07.201910:49:13
dc.date.accessioned2019-07-10T19:49:38Z
dc.date.available10.07.201910:49:13
dc.date.available2019-07-10T19:49:38Z
dc.date.issued2019en_US
dc.identifier.citationSohail, A., Younas, M., Bhatti, Y., Li, Z., Tunç, S. ve Abid, M. (2019). Analysis of trabecular bone mechanics using machine learning. Evolutionary Bioinformatics, 15. https://dx.doi.org/10.1177/1176934318825084en_US
dc.identifier.issn1176-9343
dc.identifier.urihttps://dx.doi.org/10.1177/1176934318825084
dc.identifier.urihttps://hdl.handle.net/20.500.12511/1694
dc.descriptionWOS: 000464252300001en_US
dc.descriptionPubMed ID: 30936677en_US
dc.description.abstractBone remodeling is a dynamic process, and mutliphase analysis incorporated with the forecasting algorithm can help the biologists and orthopedics to interpret the laboratory generated results and to apply them in improving applications in the fields of "drug design, treatment, and therapy" of diseased bones. The metastasized bone microenvironment has always remained a challenging puzzle for the researchers. A multiphase computational model is interfaced with the artificial intelligence algorithm in a hybrid manner during this research. Trabecular surface remodeling is presented in this article, with the aid of video graphic footage, and the associated parametric thresholds are derived from artificial intelligence and clinical data.en_US
dc.description.sponsorshipScience Technology Development Fund, MSAR [078/2015/A3, 122/2017/A3]en_US
dc.description.sponsorshipThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported in part by the Science Technology Development Fund, MSAR, under grant nos 078/2015/A3 and 122/2017/A3.en_US
dc.language.isoengen_US
dc.publisherSage Publications Ltden_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://www.creativecommons.org/licenses/by-nc/4.0/*
dc.subjectFerrofluidsen_US
dc.subjectNanomedicineen_US
dc.subjectDrug Targetingen_US
dc.subjectHyperthermiaen_US
dc.titleAnalysis of trabecular bone mechanics using machine learningen_US
dc.typearticleen_US
dc.relation.ispartofEvolutionary Bioinformaticsen_US
dc.departmentİstanbul Medipol Üniversitesi, İMÜ Meslek Yüksekokulu, Fizyoterapi Ana Bilim Dalıen_US
dc.identifier.volume15en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1177/1176934318825084en_US
dc.identifier.wosqualityQ4en_US
dc.identifier.scopusqualityQ2en_US


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