Analysis of Trabecular Bone Mechanics Using Machine Learning. (March 2019)

• Record Type: Journal Article
• Authors: Sohail, Ayesha; Younas, Muhammad; Bhatti, Yousaf; Li, Zhiwu; Tunç, Sümeyye; Abid, Muhammad
• Is Part Of: Evolutionary bioinformatics online. Volume 15(2019)
• Publication Date: 2019-03
• Subjects: ferrofluids -- nanomedicine -- drug targeting -- hyperthermia; Bioinformatics -- Periodicals; Evolutionary computation -- Periodicals; Genetic programming (Computer science) -- Periodicals; Computational Biology; Evolution, Molecular; Bioinformatics; Electronic journals; Periodicals; Fulltext; Internet Resources; Periodicals; Periodicals; 576.8
• DOI: 10.1177/1176934318825084
• Languages: English
• ISSNs: 1176-9343

Abstract

"Bone 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.