The phrase "abnormality detection is" is correct and usable in written English.
You can use it when discussing the process or concept of identifying irregularities or anomalies in data or systems.
Example: "Abnormality detection is crucial in ensuring the reliability of our monitoring systems."
Alternatives: "anomaly detection is" or "irregularity identification is".
In general, approaches for abnormality detection are based on a set of observations that define the regular behaviors in a scene.
Differences in abnormality detection are expected across microarray chips due to differences in the number/density of probes, the number of CNV-specific probes, DNA preparation and quality, flux in the levels of mosaicism during expansion or passage of individual samples, and the frequent appearance of new mosaic abnormalities in transformed cell lines [ 6].
Automated methods of lung abnormality detection are attractive in that they could provide a rapid, quantifiable, and reproducible method (at least across similar scanners and scanning protocols) [ 23] to determine if a person is at an increased risk for pulmonary fibrosis.
Step 2, feature extraction, then extracts this information in order to assign it to one abnormality type using the classification method used in Step 3. Research on EEG abnormalities detection is wide and varied, but almost in all previous studies, a single channel signal analysis approach is used (see Section 1.3).
The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages.
Second, a robust supervised abnormality detection strategy is proposed.
A loss of smell or abnormalities in odor identification or detection is also seen in some degenerative diseases, like Alzheimer's.
First, an unsupervised thresholding strategy is considered, and through an experimental study the factors that affect abnormality detection performance are considered.
As there were many potential disease genes to interrogate (>700 on the X chromosome), a rapid high-throughput gene abnormality detection methodology was needed.
Even though abnormality detection can be rather effectively done with resort to acausal correlation models of the variables normal operating conditions associations, fault diagnosis and troubleshooting do require causal information.
