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With some exceptions [ 14, 15], the pace of clinical achievements in diagnostics, classification and management of epilepsy patients in veterinary practice has not been paralleled by comparable insights into epilepsy-associated tissue changes and, in particular, those underlying drug resistance.
It depends crucially on nuanced judgements made by administrators who combine their understanding of: clinical diagnostics; classification systems; how healthcare is organised; particular working practices of individual colleagues; current health policy.
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Our findings establish a new paradigm for the diagnostic classification and treatment of ameloblastomas.
Psychiatry is often criticized for making such changes, and to be sure, the basis for some additions to the diagnostic classification may be open to question.
In addition, SGB learns to select features independent from existing diagnostic classification and is thus relatively independent from human circular reasoning.
Determining the immunophenotype of hematologic malignancies is now an indispensable part of diagnostic classification, and can help to guide therapy, or to predict clinical outcome.
Insights from sequencing the genomes, exomes, or transcriptomes of healthy and diseased cells in patients are already enabling improved diagnostic classification, prognostication, and therapy selection for many diseases.
It is apparent that a reliable and valid diagnostic classification system for TMD is needed for future research.
As EEG signals are non-stationary, the conventional method of frequency analysis is not highly successful in diagnostic classification.
About 92% used an electronic record system, some type of diagnostic classification was used by 93%, and ICD based classifications by 88%.
We briefly outline the role of diagnostic classification in clinical assessment and treatment planning.
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