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Two methods for the determination of platinum group elements were established based on neutron activation analysis (NAA) and inductively coupled plasma mass spectroscopy (ICP-MS) combined with fire assay preconcentration. Their analytical sensitivity,accuracy and applicability were discussed.The detection limits (ng/g)of NAA for Ru,Rh,Pd,Os,Ir and Pt are 0.5,0.5,0.3,0.1,0.01 and 0.2,respectively.whereas those of ICP-MS are 0.1 for Ru,0.05 for Rh,0.1 for Ir and 0.1 for Pt. Thus, both are complimentary for determination of platinum group elements. By the established methods the contents of platinum group elements in five geological reference materials were determined.

In recent years, artificial intelligence (AI) technology represented by deep learning (DL) has developed rapidly, and smart medical care has become one of the most important application areas of AI. As the most accurate noninvasive test to assess myocardial blood flow, myocardial perfusion imaging (MPI) has important clinical values. At present, the use of DL algorithms to establish learning models for MPI images is still in the research stage, and more external verification and iterative updates are needed before it can be widely used in real time clinical practice. In this article, the application of DL algorithms in MPI is comprehensively elaborated to provide a basis and direction for further research.