Sentence examples for ad classification from inspiring English sources

One major limiting factor in the widespread use of nonlinear dynamic models in AD classification is the high sensitivity of available methods to algorithm parameter changes.

For Alzheimer's disease (AD) classification, Ye et al. propose a kernel-based method for integrating heterogeneous data, including tensor and AAL features from MRI images, demographic information, and genetic information [11].

The experimental results show that our method achieves an accuracy of 90.8% and an area under the ROC curve (AUC) of 94.86% for AD classification and an accuracy of 87.85% and an AUC of 92.90% for MCI classification, respectively, demonstrating a very promising performance of our method compared with the state-of-the-art methods for AD/MCI classification using MR images.

The current system of AD classification does not adequately capture the heterogeneity of these tumors and classification using clinical, pathological and gene-expression based approaches tend to be treated as separate modalities.

Among several approaches for this point, the IASLC/ATS/ERS lung AD classification has several benefits.

The importance of this new AD classification, with wide applicability, is underscored by its prognostic effect [ 5– 9].

Accuracies of 0.85, 0.79, and 0.80 were achieved for HC-AD, HC-MCI, and MCI-AD classifications, respectively, when evaluated using a blind test set.

In such cases, ad hoc classification models based upon a few visibly different peaks (e.g. near 920 and 1100 cm−1, marked with '*') perform poorly at the single-spectrum level, where noise is higher.

We used an ad hoc classification based on DSM IV that yielded differences in LOS when analyzed univariately and when it was adjusted for other variables as well.

The results from the AD tree classification procedure showed that normal and malignant tissues could be classified with an accuracy of 100% (PZ) and 94% (TZ) with only two miRNAs used in the tree.

The ad-hoc classification into "identifying data" and "other types of data" is insufficient.