دورية أكاديمية
Convolutional Neural Network-Based Digital Diagnostic Tool for the Identification of Psychosomatic Illnesses
| العنوان: | Convolutional Neural Network-Based Digital Diagnostic Tool for the Identification of Psychosomatic Illnesses |
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| المؤلفون: | Marta Narigina, Andrejs Romanovs, Yuri Merkuryev |
| المصدر: | Algorithms, Vol 17, Iss 8, p 329 (2024) |
| بيانات النشر: | MDPI AG, 2024. |
| سنة النشر: | 2024 |
| المجموعة: | LCC:Industrial engineering. Management engineering LCC:Electronic computers. Computer science |
| مصطلحات موضوعية: | convolutional neural networks, artificial intelligence, emotion recognition, psychosomatic illnesses, facial expression analysis, real-time emotion detection, Industrial engineering. Management engineering, T55.4-60.8, Electronic computers. Computer science, QA75.5-76.95 |
| الوصف: | This paper appraises convolutional neural network (CNN) models’ capabilities in emotion detection from facial expressions, seeking to aid the diagnosis of psychosomatic illnesses, typically made in clinical setups. Using the FER-2013 dataset, two CNN models were designed to detect six emotions with 64% accuracy—although not evenly distributed; they demonstrated higher effectiveness in identifying “happy” and “surprise.” The assessment was performed through several performance metrics—accuracy, precision, recall, and F1-scores—besides further validation with an additional simulated clinical environment for practicality checks. Despite showing promising levels for future use, this investigation highlights the need for extensive validation studies in clinical settings. This research underscores AI’s potential value as an adjunct to traditional diagnostic approaches while focusing on wider scope (broader datasets) plus focus (multimodal integration) areas to be considered among recommendations in forthcoming studies. This study underscores the importance of CNN models in developing psychosomatic diagnostics and promoting future development based on ethics and patient care. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1999-4893 |
| Relation: | https://www.mdpi.com/1999-4893/17/8/329; https://doaj.org/toc/1999-4893 |
| DOI: | 10.3390/a17080329 |
| URL الوصول: | https://doaj.org/article/d446ab3325a84bcc8471ac27002f4e66 |
| رقم الأكسشن: | edsdoj.446ab3325a84bcc8471ac27002f4e66 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19994893 |
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| DOI: | 10.3390/a17080329 |