To do this, we used the verbal analysis technique of Chi ([1997]), which is a variation of protocol analysis that uses discourse-based data to identify structural features of human cognition.
2. We evaluate our method on both instance-based data and network-based data to identify system components related to three target phenotypes: biohydrogen production, motility, and cancer.
In this study, we use population-based data to identify and characterize spatial clusters of overweight (BMI≥25) and hypertension in a typical rural South African population with high HIV prevalence, and to explore whether these clusters, of high or low prevalence, could be accounted for by established individual-level risk factors.
They were based on objective data to identify populations of people with a sickness absence.
Our analysis was based, however, on dimensional data to identify the relevant symptom domains across the population as a whole and there was sufficiently high endorsement of constituent items to detect coherent individual factors as proposed in the formulation of C-PTSD.
This paper investigates the potential for using quantitative applications of statistical models of habitat suitability based on marine animal tracking data to identify key feeding areas.
Using lesion masks and behavioral data from a previous study on RHI failure in acute stroke patients, we here employed lesion network-symptom-mapping (LNSM) based on normative functional connectome data to identify lesion-dependent network connectivity related to the experience of self-attribution of an artificial hand in the RHI paradigm.
A weighted gene coexpression network analysis was then performed based on the microarray expression data to identify distinct coexpression modules corresponding to the clusters of correlated genes (Langfelder and Horvath 2008).
Whereas, the traditional model based control approach uses the measured data to identify the plant model firstly, and then uses the model to design and analyze the controller design based on this identified model.
This study, however, did not aim to develop actionable surveillance systems, produce predictive models of infectious disease based on internet-based data or to identify the best search terms for use in these models.
To avoid such shortcoming occurring in the EHR data, literature based analysis to identify information about family history will be one of the solutions.
