Background/aim: Despite the advances in oncology and cancer treatment over the past decades, cancer remains one of the deadliest diseases. This study focuses on further understanding the complex nature of cancer by using mathematical tumor modeling to understand, capture as best as possible, and describe its complex dynamics under chemotherapy treatment.
Materials And Methods: Focusing on autoregressive with exogenous inputs, i.
Purpose: The detection of where an organ starts and where it ends is achievable and, since this information can be delivered in real time, it could be quite important for several reasons. For one, by having the practical knowledge of the Wireless Endoscopic Capsule (WEC) transition through an organ's domain, we are able to align and control the endoscopic operation with any other possible protocol, i.e.
View Article and Find Full Text PDFBackground/aim: Mathematical models have long been considered as important tools in cancer biology and therapy. Herein, we present an advanced non-linear mathematical model that can predict accurately the effect of an anticancer agent on the growth of a solid tumor.
Materials And Methods: Advanced non-linear mathematical optimization techniques and human-to-mouse experimental data were used to develop a tumor growth inhibition (TGI) estimation model.
We present a method for detecting and studying neoplasia-specific functional and structural features through the combination of in vivo dynamic imaging, in silico modeling and global sensitivity analysis. We particularly present the case of cervical epithelium interacting with acetic acid solution, which is employed as an optical biomarker. The in vivo measured dynamic scattering characteristics are strongly correlated with the output of the biomarker's pharmacokinetic model that we have developed.
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