Application of artificial intelligence in the diagnosis and prevention of occupational mesothelioma: A review study

سال انتشار: 1404
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 155

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شناسه ملی سند علمی:

AIMS02_173

تاریخ نمایه سازی: 29 تیر 1404

چکیده مقاله:

Background and Aims: Early detection of occupational diseases is important because most of the occupational diseases are identified as soon as possible and by taking appropriate preventive and therapeutic measures, they can be prevented from progressing to severe and incurable stages and from causing permanent disability to the person. This review study aimed to investigate the application of artificial intelligence in the diagnosis and prevention of occupational mesothelioma. Methods: This review study used ۱۵ articles published between ۲۰۱۴ and ۲۰۲۴. The aim of this review study was to investigate the Application of artificial intelligence in the diagnosis and prevention of occupational mesothelioma using the databases Google Scholar, Science Direct, PubMed, ResearchGate, and Springer. Results: The results of various studies show that various artificial intelligence-based methods are used to diagnose mesothelioma. These methods include support vector machines, decision trees, multilayer perceptron or feed-forward neural networks, j۴۸ algorithm, bagging algorithm, logistic regression and gradient boosting algorithm, which have ۱۰۰% accuracy compared to other methods for diagnosing mesothelioma and Other algorithms had an accuracy lower than ۱۰۰%. Conclusion: The results of this review study showed that artificial intelligence algorithms are useful for early detection and prevention of mesothelioma, which helps in the early and early diagnosis of this deadly disease. Keywords: Artificial Intelligence, Occupational Mesothelioma, Occupational Exposure, Prevention

نویسندگان

Ayoub Ghanbary Sartang

The Health Deputy, Department of Occupational Health Engineering, Abadan University of Medical Sciences, Khuzestan, Iran.

Shokat Tajzadeh

The Health Deputy, Department of Occupational Health Engineering, Abadan University of Medical Sciences, Khuzestan, Iran.

Seyed Ahmad Mousavi Asl

The Health Deputy, Department of Occupational Health Engineering, Abadan University of Medical Sciences, Khuzestan, Iran.

Reza Fallahi

The Health Deputy, Department of Occupational Health Engineering, Abadan University of Medical Sciences, Khuzestan, Iran.