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With the advances of data-driven machine learning research, a wide variety of prediction problems have been tackled. It has become critical to explore how machine learning and specifically deep learning methods can be exploited to analyse healthcare data. A major limitation of existing methods has been the focus on grid-like data; however, the structure of physiological recordings are often irregular and unordered, which makes it difficult to conceptualise them as a matrix. As such, graph neural networks have attracted significant attention by exploiting implicit information that resides in a biological system, with interacting nodes connected by edges whose weights can be determined by either temporal associations or anatomical junctions. In this survey, we thoroughly review the different types of graph architectures and their applications in healthcare. We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis. We also outline the limitations of existing techniques and discuss potential directions for future research.

ABSTRACT:A study was conducted to determine the effect of different concentrations of lead and cadmium on seed germination and seedling growth of Leucaena leucocephala. Seed were grown under laboratory conditions at 25, 50, 75 and 100 ppm of metal ions of lead and cadmium. Both lead and cadmium treatments showed toxic effects on various growth indices of L. leucocephala. Increasing the concentration of lead to 75 ppm, significantly (p<0.05) decreased seed germination as compared to control. Seedling and root growth was significantly (p<0.05) reduced at 50 ppm treatment of lead. Seed germination and root length significantly (p<0.05) decreased at 50 ppm treatment of cadmium as compared to control. The seedling dry weight also significantly (p<0.05) reduced at 25 ppm treatment of lead and cadmium. Cadmium treatment at 100 ppm showed comparatively pronounced effects in L. leucocephala seedlings as compared to lead. The results of the study suggest that due to better metal tolerance indices there is a possibility of growing L. leucocephala in areas contaminated with lead and cadmium. @ JASEM