The use of classification and regression tree to predict 15-year survival in community-dwelling older people

Previous research has identified various risk factors for mortality in older people. The aim of this paper was to use Classification and Regression Tree to predict 15-year survival in community-dwelling older people. Data were obtained from a United Kingdom representative sample of 1042 community-dwelling people aged 65 and over. Outcome was time from 1985 interview to death or censorship on February 29, 2000. Classification and Regression Tree is a non-parametric technique widely used in medical domain classification. We applied CART to the set of risk-factors identified in a previous research. The selected CART model is based on age, dose of drug prescribed and handgrip measures. It predicts survival with a sensitivity rate of 76.3% and a specificity rate of 66.3%. The selection of variables are consistent with previous research. Finally, we observed the range of risk factors and their combination associated with increased and decreased mortality

An Integrated Approach in Risk Management Process for Identifying Information Security Threats using Medical Research Design

In this paper, we attempt to introduce a new method for performing risk analysis studies by effectively adopting and adapting medical research design namely a prospective cohort study based survival analysis approach into risk management process framework. Under survival analysis approach, a method which is known as Cox Proportional Hazards (PH) Model will be applied in order to identify potential information security threats. The risk management process in this research will be based on Australian/New Zealand Standard for Risk Management (AS/NZS ISO 31000:2009). AS/NZS ISO 31000:2009 provides a sequencing of the core part of the risk management process namely establishing the context, risk identification, risk analysis, risk evaluation and risk treatment. Moreover, it seems that the integration of risk management process with medical approach indeed brings very useful new insights. Thus, the contribution of the paper will be introducing a new method for performing a risk analysis studies in information security domain

The use of Cox regression and genetic algorithm (CoRGA) for identifying risk factors for mortality in older people

The increase in the proportion and number of older people in developed countries has resulted in research investigating risk factors for adverse health outcomes, including mortality. However, research has been limited by the range of risk factors included in regression models. This is partly because traditional statistical methods and software packages allow a restricted number of variables and combinations of variables. This article describes ongoing research to overcome these limitations through the CoRGA program, which combines Cox regression with a genetic algorithm for the variable selection process. CoRGA was used to try and identify the best combination of risk factors for 4-year all-cause mortality. The combination of 10 risk factors identified by CoRGA included both known and new risk factors for mortality in older people. Further research is seeking to develop the program further and to identify further risk factors for all-cause mortality in older people