Academic Journal

Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs)

التفاصيل البيبلوغرافية
العنوان: Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs)
المؤلفون: Mareike Buhl
المصدر: Diagnostics, Vol 12, Iss 2, p 463 (2022)
بيانات النشر: MDPI AG, 2022.
سنة النشر: 2022
المجموعة: LCC:Medicine (General)
مصطلحات موضوعية: CDSS, audiology, precision medicine, interpretability, machine learning, expert knowledge, Medicine (General), R5-920
الوصف: Common Audiological Functional Parameters (CAFPAs) were previously introduced as abstract, measurement-independent representation of audiological knowledge, and expert-estimated CAFPAs were shown to be applicable as an interpretable intermediate layer in a clinical decision support system (CDSS). Prediction models for CAFPAs were built based on expert knowledge and one audiological database to allow for data-driven estimation of CAFPAs for new, individual patients for whom no expert-estimated CAFPAs are available. Based on the combination of these components, the current study explores the feasibility of constructing a CDSS which is as interpretable as expert knowledge-based classification and as data-driven as machine learning-based classification. To test this hypothesis, the current study investigated the equivalence in performance of predicted CAFPAs compared to expert-estimated CAFPAs in an audiological classification task, analyzed the importance of different CAFPAs for high and comparable performance, and derived explanations for differences in classified categories. Results show that the combination of predicted CAFPAs and statistical classification enables to build an interpretable but data-driven CDSS. The classification provides good accuracy, with most categories being correctly classified, while some confusions can be explained by the properties of the employed database. This could be improved by including additional databases in the CDSS, which is possible within the presented framework.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2075-4418
Relation: https://www.mdpi.com/2075-4418/12/2/463; https://doaj.org/toc/2075-4418
DOI: 10.3390/diagnostics12020463
URL الوصول: https://doaj.org/article/9b6ee0a462174132926a0f3841905c3d
رقم الانضمام: edsdoj.9b6ee0a462174132926a0f3841905c3d
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20754418
DOI:10.3390/diagnostics12020463