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EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency.
This study was carried out by the PSICOST research association and the DEFDEP (DEFintion of DEPendency) group on a sample of 306 patients with schizophrenia [ 19] and it included the development of a case mix based on functional dependency.
EbCA-DEA has been used to assess technical efficiency of health care areas (case study 1) and ClBR has been used to generate a case-mix of schizophrenia based on functional dependency (case study 2).
The EbCA approach has been incorporated in two very different methods (Data Envelopment Analysis and statistical clustering) in two separate studies of integrated mental health care: benchmarking and technical efficiency of integrated mental health care [ 13], and case-mix for schizophrenia based on functional dependency [ 24].
EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by EbCA-Data Envelopment Analysis (EbCA-DEA), and 2) Case-mix of schizophrenia based on functional dependency using Clustering Based on Rules (ClBR).
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The functional gene repertoires were based on functional assignments of the metagenomes using the FOAM9 database.
Classifications are based on functional mobility.
One promising approach is constraint-based data cleansing, which is based on traditional functional dependencies (FDs) or recently proposed conditional functional dependencies (CFDs) [1].
A normal form is a way of classifying a table based on the functional dependencies (FDs) in it.
This may explain the fact that, in many European countries, the legislation on functional dependency is theoretically based on ICF while it uses the ADL approach for the assessment and for the development of eligibility criteria to different levels of care provision [ 4].
In this paper, we focus on functional dependency (FD), an important type of data dependency constraints, and study the security threats by the adversarial FDs.
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based on temporal dependency
based on mutual dependency
based on functional class
based on functional outcome
based on oncogenic dependency
based on strategic dependency
based on functional information
based on spatial dependency
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based on contextual dependency
based on functional aggregation
based on functional impairment
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based on functional similarity
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based on functional transformation
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