HLM classification seems to be easily applied in the real world and valuable for balancing economic resources with the clinical complexity of patients.
The 3-digit industrial classification seems to be the level at which MAR and Jacobs effects are undistinguishable from one another, and this is often exacerbated by a high level of geographical aggregation.
The most widely cited classification seems to be the one by Xiang and Gretzel [4] who divide social media into (1) virtual communities, (2) reviews, (3) blogs, (4) social networks and (5) media sharing sites.
In 1980, validity of the DOT was already challenged: the classification seemed to be designed for unskilled factory and physical laboring jobs.
The proportion of items for the classification seemed to be similar between the two libraries as a whole.
In severely injured patients, the SI-based classification seems to be equivalent to BD with respect to discriminate the need for early blood product transfusion.
Although a trend that EBV positivity is associated with increased age is observed, age cutoff (>50 years) in definition in 2008 WHO lymphoma classification seems to be arbitrary.
There are two isolates for which serological classification seemed to be in contrast to MLST identification, i.e. INT 46, L. interrogans serovar Lyme and SAN 18, L. santarosai serovar Copenhageni.
As a fundamental finding, TNM classification seems to be the strongest prognostic factor in neoadjuvantly treated patients, despite being based on the data from primary resected patients (Gertler et al, 2011; Reim et al, 2013).
Instead, the classification seems to be based on how the network operates: low complexity hospitals aim to improve geographical coverage, while high complexity hospitals are regional or reference centres to which low complexity hospitals refer patients who require a more complex level of care.
