Academic Journal
Utilizing ChatGPT for Curriculum Learning in Developing a Clinical Grade Pneumothorax Detection Model: A Multisite Validation Study
| العنوان: | Utilizing ChatGPT for Curriculum Learning in Developing a Clinical Grade Pneumothorax Detection Model: A Multisite Validation Study |
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| المؤلفون: | Joseph Chang, Kuan-Jung Lee, Ti-Hao Wang, Chung-Ming Chen |
| المصدر: | Journal of Clinical Medicine, Vol 13, Iss 14, p 4042 (2024) |
| بيانات النشر: | MDPI AG |
| سنة النشر: | 2024 |
| المجموعة: | Directory of Open Access Journals: DOAJ Articles |
| مصطلحات موضوعية: | artificial intelligence, deep learning, curriculum learning, pneumothorax, Medicine |
| الوصف: | Background : Pneumothorax detection is often challenging, particularly when radiographic features are subtle. This study introduces a deep learning model that integrates curriculum learning and ChatGPT to enhance the detection of pneumothorax in chest X-rays. Methods : The model training began with large, easily detectable pneumothoraces, gradually incorporating smaller, more complex cases to prevent performance plateauing. The training dataset comprised 6445 anonymized radiographs, validated across multiple sites, and further tested for generalizability in diverse clinical subgroups. Performance metrics were analyzed using descriptive statistics. Results : The model achieved a sensitivity of 0.97 and a specificity of 0.97, with an area under the curve (AUC) of 0.98, demonstrating a performance comparable to that of many FDA-approved devices. Conclusions: This study suggests that a structured approach to training deep learning models, through curriculum learning and enhanced data extraction via natural language processing, can facilitate and improve the training of AI models for pneumothorax detection. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2077-0383 |
| Relation: | https://www.mdpi.com/2077-0383/13/14/4042; https://doaj.org/toc/2077-0383; https://doaj.org/article/0de20618fca14d61ac964cb142e1efbf |
| DOI: | 10.3390/jcm13144042 |
| الاتاحة: | https://doi.org/10.3390/jcm13144042 https://doaj.org/article/0de20618fca14d61ac964cb142e1efbf |
| رقم الانضمام: | edsbas.BBF89ED7 |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 20770383 |
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| DOI: | 10.3390/jcm13144042 |