A machine learning approach for optimal disassembly planning
International Journal of Computer Integrated Manufacturing - THE CHALLENGES OF MANUFACTURING IN THE GLOBALLY INTEGRATED ECONOMY. GUEST EDITOR: ROBIN G. QIU
A variational approximation for Bayesian networks with discrete and continuous latent variables
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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Making context based and pertinent clinical knowledge to the point of care that is most appropriate for individuals becomes an unprecedented challenge to bring American closer than ever to the promise of personalized health care. This paper, from the engineering perspective, presents a new conceptual framework that keeps patients in focus and continuously incorporates new knowledge to improve quality and value in healthcare. A colored Petri net model linked with a hybrid Bayesian network is then proposed to address two imperative issues in the development of a learning healthcare system: (1) mathematical representation of the complex health care processes to ensure shared decision-making; and (2) exploration and exploitation of knowledge about patients and health outcome measures for continuous improvement.