A review of dynamical systems approaches for the detection of chaotic attractors in cancer networks.
作者： Abicumaran Uthamacumaran
DOI: 10.1016/J.PATTER.2021.100226
关键词: State space 、 Network medicine 、 Attractor 、 DECIPHER 、 Machine learning 、 Inference 、 Computer science 、 Complex system 、 Artificial intelligence 、 Dynamical systems theory 、 Causality
摘要: Cancers are complex dynamical systems. They remain the leading cause of disease-related pediatric mortality in North America. To overcome this burden, we must decipher the state …
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