The phrase "abnormality classification" is correct and usable in written English.
It can be used in contexts related to medical, psychological, or statistical analysis where categorizing abnormalities is necessary.
Example: "The study focused on the abnormality classification of various genetic disorders to better understand their impact on patient health."
Alternatives: "anomaly categorization" or "irregularity classification".
Each individual specimen was examined by a trained technician and classified according to a case definition adapted from a well-established amphibian limb abnormality classification scheme (Meteyer et al. 2000).
Abnormal frogs were euthanized with tricaine methanesulfonate (MS-222; Argent Chemical Laboratories, Redmond, WA), photographed, and sent to the U.S. Geological Survey, National Wildlife Health Center, or Ball State University for radiographs to aid in abnormality classification.
In addition to different age profiles, comparison between studies is complicated by different HPV testing regimes (since tests detect different strains and vary in performance characteristics; Kulmala et al, 2004; Bosch and Iftner, 2005) and UK/USA differences in cytological abnormality classification.
We used the European Surveillance of Congenital Abnormalities Classification (EUROCAT) [ 22] to categorize CAs as minor and major, and excluded chromosome aberrations, genetic syndromes and microdeletions, teratogenic syndrome.
We divided them into categories according to the European Surveillance of Congenital Abnormalities Classifications (EUROCAT) criteria (part 7 of the former EUROCAT Guide 1.2).. CAs were classified into subgroups after excluding minor CAs with lesser medical, functional or cosmetic importance, as defined by EUROCAT.
As a result, the accuracies of six SVM modules used for detection of abnormality and classification of six heart disorders showed 71 98.9% for THVs=10 90% and 81.2 99.6% for THVs=10 50% with respect to each of SVM modules.
Even though we can quantify these abnormalities, a classification system has yet to be developed.
More precisely, this article reports the results of a study on EEG abnormalities detection and classification in the case of mono-channel T-F analysis first, and then, the EEG abnormalities sources localization in the case of multichannel T-F analysis.
Figure 4 EEG-based automated abnormalities detection and classification scheme: (a) Block diagram of traditional single analysis.
These methods described above can be assessed in terms of performance against quality criteria for EEG abnormalities detection and classification.
Although, the EEG abnormalities detection and classification system receives an input of more than one EEG channel, the analysis is made for a single channel only.
