Quality of life declines in patients on PD over time. Certain aspects of QoL are especially poor in Asian and male patients. This study suggests that further research is necessary to determine the effects of interventions directed at enhancing emotional and social support.
Experimental datasets in bioengineering are commonly limited in size, thus rendering Machine Learning (ML) impractical for predictive modelling. Novel techniques of multiple runs for model development and surrogate data analysis for model validation are suggested for prediction of biomedical outcomes based on small datasets for classification and regression tasks. The proposed framework was applied to designing a Neural Network model for osteoarthritic bone fracture risk stratification, and a Decision Tree model for prediction of antibody-mediated kidney transplant rejection. Despite the small datasets (35 bone specimens and 80 kidney transplants), the two models achieved high accuracy of 98.3% and 85%, respectively.
These data raise the possibility that, in high immunologic risk patients undergoing Ai transplantation, the presence of elevated pretransplantation serum BAFF might identify those at increased risk of AMR. BAFF neutralization may be an interesting therapeutic strategy to explore in these patients, particularly because such agents are available and have already been used in the treatment of autoimmunity.
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