ARCHETYPE ID | openEHR-EHR-OBSERVATION.common_audiological_functional_parameters.v3 |
Concept | common_audiological_functional_parameters |
Description | A set of functional parameters that provides an abstract description of all relevant functional aspects of the human auditory system, with interpretation ranging from "normal" (0) to "maximally impaired" (1). The list of possible functional aspects corresponds to the definition of Buhl et al. (2019). |
Use | Use to summarize data from audiological tests that were performed with humans in hearing aid acoustician, ENT physician, or research scenarios. CAFPAs can be estimated by human experts or predicted by machine learning algorithms. |
Misuse | Not to be used to directly save measurement results (corresponding to a test corresponding to the respective functional parameter). |
Purpose | To summarize data from different audiological tests (as performed in a certain clinic/database) in an independent and abstract representation of the human auditory system. Thereby, the CAFPAs are independent from the exact used tests for characterizing certain aspects of hearing loss in different clinical or research databases, and can be used to compare data from different databases. |
References | Buhl M, Warzybok A, Schädler MR, Lenarz T, Majdani O, Kollmeier B. Common Audiological Functional Parameters (CAFPAs): statistical and compact representation of rehabilitative audiological classification based on expert knowledge. Int J Audiol. 2019 Apr;58(4):231-245. doi: 10.1080/14992027.2018.1554912. PMID: 30900518. Buhl M, Warzybok A, Schädler MR, Majdani O, Kollmeier B. Common Audiological Functional Parameters (CAFPAs) for single patient cases: deriving statistical models from an expert-labelled data set. Int J Audiol. 2020 Jul;59(7):534-547. doi: 10.1080/14992027.2020.1728401. Epub 2020 Feb 24. PMID: 32091289. Saak SK, Hildebrandt A, Kollmeier B, Buhl M. Predicting Common Audiological Functional Parameters (CAFPAs) as Interpretable Intermediate Representation in a Clinical Decision-Support System for Audiology. Front Digit Health. 2020 Dec 15;2:596433. doi: 10.3389/fdgth.2020.596433. PMID: 34713064; PMCID: PMC8521966. Buhl M, Akin G, Saak S, Eysholdt U, Radeloff A, Kollmeier B, Hildebrandt A. Expert validation of prediction models for a clinical decision-support system in audiology. Front Neurol. 2022 Aug 23;13:960012. doi: 10.3389/fneur.2022.960012. PMID: 36081868; PMCID: PMC9446152. |
Copyright | © openEHR Foundation, HiGHmed |
Authors | Author name: Mareike Buhl, Samira Saak Organisation: Institut de l'Audition, Institut Pasteur, Paris, France / University of Oldenburg and Cluster of Excellence Hearing4all, Germany Email: mareike.buhl@pasteur.fr Date originally authored: 2023-06-19 |
Other Details Language | Author name: Mareike Buhl, Samira Saak Organisation: Institut de l'Audition, Institut Pasteur, Paris, France / University of Oldenburg and Cluster of Excellence Hearing4all, Germany Email: mareike.buhl@pasteur.fr Date originally authored: 2023-06-19 |
OtherDetails Language Independent | {licence=This work is licensed under the Creative Commons Attribution-ShareAlike 3.0 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/., custodian_organisation=HiGHmed, references=Buhl M, Warzybok A, Schädler MR, Lenarz T, Majdani O, Kollmeier B. Common Audiological Functional Parameters (CAFPAs): statistical and compact representation of rehabilitative audiological classification based on expert knowledge. Int J Audiol. 2019 Apr;58(4):231-245. doi: 10.1080/14992027.2018.1554912. PMID: 30900518. Buhl M, Warzybok A, Schädler MR, Majdani O, Kollmeier B. Common Audiological Functional Parameters (CAFPAs) for single patient cases: deriving statistical models from an expert-labelled data set. Int J Audiol. 2020 Jul;59(7):534-547. doi: 10.1080/14992027.2020.1728401. Epub 2020 Feb 24. PMID: 32091289. Saak SK, Hildebrandt A, Kollmeier B, Buhl M. Predicting Common Audiological Functional Parameters (CAFPAs) as Interpretable Intermediate Representation in a Clinical Decision-Support System for Audiology. Front Digit Health. 2020 Dec 15;2:596433. doi: 10.3389/fdgth.2020.596433. PMID: 34713064; PMCID: PMC8521966. Buhl M, Akin G, Saak S, Eysholdt U, Radeloff A, Kollmeier B, Hildebrandt A. Expert validation of prediction models for a clinical decision-support system in audiology. Front Neurol. 2022 Aug 23;13:960012. doi: 10.3389/fneur.2022.960012. PMID: 36081868; PMCID: PMC9446152., current_contact=Mareike Buhl, Institut de l'Audition, mareike.buhl@pasteur.fr, original_namespace=org.highmed, original_publisher=HiGHmed, custodian_namespace=org.highmed, MD5-CAM-1.0.1=D655E3AB1111C2DACFAF7B0783FB1F1B, build_uid=65914547-77cc-4b1f-b237-642e088cdaf9, revision=3.0.0-alpha} |
Keywords | audiology, hearing loss, functional aspect, abstract representation, ... |
Lifecycle | in_development |
UID | cfef84ea-5157-42c9-a749-e2d11b2f4e6d |
Language used | en |
Citeable Identifier | 1246.145.2160 |
Revision Number | 3.0.0-alpha |
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