Semantic Online Analytical Processing
Semantic Online Analytical Processing - Related Videos
13:37
Language: The N400 in Semantic Incongruity
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2023
Source: Laboratories of Sarah I. Gimbel and Jonas T. Kaplan— University of Southern California Understanding language is one of the most complex cognitive tasks that humans are capable of. Given the incredible amount of possible choices when combining individual words to form meaning in sentences, it is crucial that the brain is able to identify when words form coherent combinations and when an anomaly appears that undermines meaning. Extensive research has shown that certain scalp-recorded...
08:17
A Semantic Priming Event-related Potential (ERP) Task to Study Lexico-semantic and Visuo-semantic Processing in Autism Spectrum Disorder
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Cited by 4 •
2018
This paper describes a semantic priming ERP task using within-modality pairs of pictures and words to investigate semantic processing in individuals with autism spectrum disorder (ASD).
05:38
Interaction between Phonological and Semantic Processes in Visual Word Recognition using Electrophysiology
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Cited by 4 •
2021
We present a protocol to explore the relative activation sequence of phonology and semantics in visual word recognition. The results show that consistent with interactive accounts, semantic and phonological representations may be processed interactively, and higher-level linguistic representations may affect early processing.
09:44
Methods to Test Visual Attention Online
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Cited by 26 •
2015
To replicate laboratory settings, online data collection methods for visual tasks require tight control over stimulus presentation. We outline methods for the use of a web application to collect performance data on two tests of visual attention.
05:40
Fabricating Cotton Analytical Devices
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2016
To investigate simple fabrication approaches for multiple assay needs, we created a fluid-absorbing channel system made of cotton material. This device was used to establish a multiple detection platform, and solve contamination issues that commonly affect lateral flow-based biomedical devices, for clinical urinalysis of nitrite, total protein, and urobilinogen.
FAQs
Semantic Online Analytical Processing depends on a semantic layer that explicitly organizes measures, dimensions, relationships, and business rules. Measures represent values being analyzed, dimensions provide perspectives for grouping information, relationships connect related concepts, and rules preserve agreed interpretations. This structure lets users examine multidimensional data through medically meaningful concepts rather than database-specific arrangements.
Business rules establish how concepts should be interpreted across integrated datasets. When an analysis spans clinical, laboratory, demographic, and operational information, shared rules help preserve query consistency instead of leaving each user to interpret technical structures independently. That consistency makes comparisons across patients, diagnoses, treatments, or time periods more dependable.
Relationships determine how different dimensions can be examined together. In a medical analysis, linking concepts such as patients, diagnoses, treatments, and time periods allows a query to move beyond a single dataset or category. The value lies in analyzing connected clinical contexts through a common conceptual structure rather than treating each information source as isolated.
A practical workflow starts by identifying relevant datasets and the concepts needed for analysis, then representing those concepts through measures, dimensions, relationships, and business rules. Users can subsequently query the integrated information through the semantic layer, selecting patient, diagnosis, treatment, or time perspectives without handling underlying database complexity. This supports repeatable multidimensional investigations.
Combining clinical, laboratory, demographic, and operational data supports analyses that no single category can provide alone. Medical teams can examine cohorts while relating diagnoses, treatments, patient characteristics, and time periods. This integrated view is relevant to quality assessment and population health research because it connects multiple dimensions of care within a consistent analytical setting.
The approach is useful when decisions require evidence across more than one medical dimension. Cohort analysis can organize patients for comparison, quality assessment can examine patterns across relevant categories, and population health research can study broader groups. Because queries use consistent meanings, findings can inform evidence-based decision-making without requiring each user to manage underlying data structures.