Sentence examples for more advanced classification from inspiring English sources

Moreover, more advanced classification methods will be investigated.

While we can not rule out that more advanced classification methodologies and/or better distance metrics might be applicable in order to improve prediction accuracy, it is quite interesting and exciting that standard, simple methods are quite accurate and useful.

However, a more advanced classification may further specify illness course (episodic, chronic with increasing impairment, chronic with stable impairment, etc.

In addition, more advanced classification algorithms and techniques will be considered, including advanced artificial neural network architectures, such as higher order and spiking neural networks.

30 Most recent binding site classification methods now use a combination of both sequence data and structural properties and as such require more advanced classification methodologies such as Support Vector Machines, Bayesian Networks, Neural Networks, Hidden Markov Models or Conditional Random Fields.

Of the patients in the group with high-copies H.Pylori, neoplasms were more frequently located in the upper stomach (51.2% vs 18%), and a more lower pN classification(N0/N1) was observed while a more advanced pN classification(N0/N1) was seen in the group with low-copies H.Pylori.

Those who did not receive ENI also tended to have more advanced T classification and a triple-negative phenotype.

15, 16 This leads to the potential shifting of patients into a more advanced nodal classification simply by investigating more lymph nodes.

Loss of membranous CD44s was linked to more advanced T classification (P=0.014), lymph node involvement (P=0.002), the presence of vascular invasion (P=0.048), left-sidedness (P=0.008), and an infiltrating tumour border (P=0.002).

Loss of membranous CD166 was linked to more advanced T classification (P=0.002), lymph node metastasis (P=0.004), an infiltrating tumour border configuration (P<0.001), and worse overall survival compared with patients with CD166 overexpression (P=0.015; Figure 2A).

Statistical procedures included conventional linear analysis and more advanced techniques for classification of lesions in benign and malignant.