Sohail, AyeshaYounas, MuhammadBhatti, YousafLi, ZhiwuTunç, SümeyyeAbid, Muhammad10.07.20192019-07-1010.07.20192019-07-102019Sohail, 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/10.1177/11769343188250841176-9343https://dx.doi.org/10.1177/1176934318825084https://hdl.handle.net/20.500.12511/1694WOS: 000464252300001PubMed ID: 30936677Bone 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.enAttribution-NonCommercial 4.0 Internationalinfo:eu-repo/semantics/openAccessFerrofluidsNanomedicineDrug TargetingHyperthermiaArticle1510.1177/1176934318825084Q4Q2