Diagnosis of Covid-19 by Machine Learning from Blood Test

Abstract

Artificial intelligence technologies that are used in healthcare are led by machine learning methods and are effective in many areas such as early diagnosis, assessment and decision making. These technologies have shown significant success in diagnosing and monitoring the course of Covid-19 disease, which has caused a global epidemic. In this paper, studies that experimented with machine learning methods in diagnosing the disease, determining its severity and level of contagion were reviewed. In the review process, in order to take all of the experiences into account and reach meaningful outcomes, some missing data were completed and similar studies were combined so as to make the results comparable. In addition, F-β criteria were included in the evaluation metrics based on error cost analysis. The artificial neural network method was found to be successful in diagnosing the disease and determining its severity. There is not yet a reliable model that can be used, to determine which method is better in determining the infection rate.

Keywords

• Machine learning
• Covid-19
• real-time reverse transcription polymerase chain reaction
• blood analysis.

Makine Öğrenmesi Yöntemleri ile Kan Tahlilinden Covid-19 Teşhisi

Abstract

Sağlık alanında kullanılan yapay zekâ teknolojileri, makine öğrenmesi yöntemleri öncülüğünde; erken tanı, değerlendirme ve karar verme gibi pek çok alanda etkili olmaktadır. Bu teknolojiler küresel bir salgına neden olmuş olan Covid-19 hastalığına tanı koymak ve gelişiminin izlenmesinde önemli başarı göstermiştir. Bu çalışmada hastalığı tanılamak ile birlikte, şiddetini ve bulaşıcılık düzeyinin saptanmasında, makine öğrenme yöntemlerini deneyimleyen çalışmalar taranmıştır. Bu incelemede tüm deneyimlerin dikkate alınması ve anlamlı sonuçlara ulaşılması amacıyla bazı eksik veriler tamamlanmış benzer çalışmalar birleştirilmiş ve sonuçlar karşılaştırılabilir hale getirilmiştir. Ayrıca hata maliyet analizini temel alarak değerlendirme ölçülerine F-β ölçütleri de katılmıştır. Yapay sinir ağı yönteminin hastalığın tanılanması ve şiddetini belirlemede başarılı olduğu görülmektedir. Bulaşma hızının belirlenmesinde ise hangi yöntemin daha iyi olduğunu belirlemekte kullanılabilecek güvenilir bir model henüz yoktur.

Keywords

• Makine öğrenmesi
• Covid‐19
• gerçek‐zamanlı ters transkripsiyon polimeraz zincir reaksiyonu
• kan sayımı.

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