چکیده مقاله
Introduction: Interstitial lung diseases ILDs are a complex group of diseases characterized by inflammation and scarring in the lung interstitium 1 Machine learning algorithms show potential in disease prediction, outcome evaluation, diagnosis, and prognosis 2 This study explores the use of these algorithms in ILD management Methods: We searched PubMed and Scopus for articles up to February 2, 2025, following the PRISMA guideline 3 Keywords included machine learning, computer vision, knowledge, deep learning, expert systems, NLP, neural networks, interstitial lung diseases, and diffuse parenchymal lung disease Four researchers reviewed titles, abstracts, and full texts, then collected data in accordance with the study's aim Results: The study included 81 articles, mainly using machine learning and deep learning for ILD management in diagnosis 76 articles, 63 33% , follow up 26, 21 66% , and prevention 17, 14 16% The most common algorithms were CNN 68, 51 90% , SVM 8, 6 10% , and RF 7, 5 34% Conclusion: This study highlights the role of machine learning and deep learning in managing ILD, including diagnosis, follow up, prevention, and treatment It shows that these algorithms are mostly used for diagnosis, especially CNN A structured approach to validate and explain these models would help clinicians develop and implement them more effectively Keywords: ILD, Machine Learning, Diagnosis, Artificial Intelligence
کلیدواژهها
نویسندگان
Aida Abolhassani
Department of Anesthesia, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Mohammad Jam'dar
Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Parnia Karimian
Department of Anesthesia, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Marsa Gholamzadeh
Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Erfan Esmaeeli
Department of Health Information Management and Medical Informatics, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
Shaghayegh Miri
Department of Anesthesia, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
شیوه ارجاع
Abolhassani, Aida and Jam'dar, Mohammad and Karimian, Parnia and Gholamzadeh, Marsa and Esmaeeli, Erfan and Miri, Shaghayegh,1404,Using artificial intelligence and machine learning algorithms for interstitial lung diseases (ILD): A systematic review,20th International Conference on Health, Treatment and Health Promotion
ارائهشده در
مجموعه مقالات بیستمین کنفرانس بین المللی بهداشت، درمان و ارتقای سلامت24 مرداد 1404