Intelligent systems and technology for integrative and predictive medicine

Abstract

One of the principal goals in medicine is to determine and implement the best treatment for patients through fastidious estimation of the effects and benefits of therapeutic procedures. The inherent complexities of physiological and pathological networks that span across orders of magnitude in time and length scales, however, represent fundamental hurdles in determining effective treatments for patients. Here we argue for a new approach, called the ACP-based approach, that combines artificial (societies), computational (experiments), and parallel (execution) methods in intelligent systems and technology for integrative and predictive medicine, or more generally, precision medicine and smart health management. The advent of artificial societies that collect the clinically relevant information in prognostics and therapeutics provides a promising platform for organizing and experimenting complex physiological systems toward integrative medicine. The ability of computational experiments to analyze distinct, interactive systems such as the host mechanisms, pathological pathways, and therapeutic strategies, as well as other factors using the artificial systems, will enable control and management through parallel execution of real and arficial systems concurrently within the integrative medicine context. The development of this framework in integrative medicine, fueled by close collaborations between physicians, engineers, and scientists, will result in preventive and predictive practices of a personal, proactive, and precise nature, including rational combinatorial treatments, adaptive therapeutics, and patient-oriented disease management.

Smart dispatching for energy internet with complex cyber‐physical‐social systems: A parallel dispatch perspective

“…This is because during the modeling of dispatching for the EI from a perspective of parallel dispatch, the traditional simulation models and simulation systems are not suitable for the construction of virtual artificial world, resulting in that we need to adopt complex system analysis methods based on big data analysis, including the artificial system based modeling methods, computational experiments and system analysis and evaluation, and parallel execution and system control and management. 10,50 3) The ACP approach to achieve KA The ACP framework proposed by Wang et al [50][51][52] is demonstrated in Figure 8, where the core of ACP approach is to decompose the virtual parts of complex CPSS into quantifiable, computable, and executable processes. The three parts included in the ACP method are briefly introduced as follows.…”

“…The steps of implementing ACP method including: (a) using artificial systems to model complex problems (physical, social, and cyber); (b) using computational experiments to analyze and evaluate complex phenomena; (c) combining artificial systems with actual systems and through virtual and real interaction, to guide and manage physical processes in a parallel execution way. 5,[50][51][52] 4) The role of KA in parallel dispatch For the implementation of parallel dispatch in the EI, KA is a crucial technique, which is mainly reflected in plug-and-play of the hardware systems and KA design of the software systems. 11,15 The parallel dispatch is represented by PDR.…”

“…In order to realize the operability of ACP method, we need to construct an execution framework of parallel systems, as illustrated in Figure 8, where we need to inspect and evaluate via VPAS, and then continuously construct artificial models and repeatedly carry out computational experiments based on the data, so as to achieve parallel execution strategies. 5,15,[50][51][52] In the above process of parallel execution, the artificial system can be regarded as an extension of traditional mathematical or analytical modeling, called a generalized knowledge model, which is the basis for realizing agility to varying degrees. Generally speaking, the artificial system can be constructed as a multilevel intelligent model via the intelligent technique such as multiagent technique, so that the system can independently optimize the model according to the environmental conditions and its own states.…”

“…The key to implementing KA is to introduce the ACP method, ie, artificial societies (A), computational experiments (C), and parallel execution (P). This is because during the modeling of dispatching for the EI from a perspective of parallel dispatch, the traditional simulation models and simulation systems are not suitable for the construction of virtual artificial world, resulting in that we need to adopt complex system analysis methods based on big data analysis, including the artificial system based modeling methods, computational experiments and system analysis and evaluation, and parallel execution and system control and management …”

“…The ACP framework proposed by Wang et al is demonstrated in Figure , where the core of ACP approach is to decompose the virtual parts of complex CPSS into quantifiable, computable, and executable processes. The three parts included in the ACP method are briefly introduced as follows…”