Akademik Veri Yönetim Sistemi
International Conference on Intelligent and Fuzzy Systems, INFUS 2021, İstanbul, Türkiye, 24 - 26 Ağustos 2021, cilt.307, ss.787-795
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.The objective of this research paper is to develop a fast pre-diagnosis support system to manage the post-acute covid-19 and to facilitate the diagnosis of a highly complicated and yet uncertain disease. The post-acute covid-19 also called “long covid” has been recently defined as a multisystem disease with ongoing signs and symptoms of covid-19 for more than four weeks after acute covid-19 infection. The recovery time for each patient is different but in most of the cases the symptoms disappear under twelve weeks. Even so, it has been registered lately that a significant number of patients have been suffering from ongoing symptoms for more than twelve weeks. There is a wide variety of symptoms and some patients may suffer from only one symptom while others may suffer from more than one at the same time. Besides, it has been discovered that post covid-19 syndrome is most probably not related to the severity of acute covid-19 infection period. Predicting post covid-19 syndrome according to some symptoms or generalizing a diagnosis for different patients is not recommended by specialists. Decision makers must incorporate many other aspects such as patient’s medical history and the nature and severity of symptoms. Decision making in such an uncertain environment is highly difficult. This study procures a Fuzzy Cognitive Maps (FCM) based model to help pre-diagnosis process of post covid-19 syndrome in Turkey. To improve the effectiveness and the robustness of FCM involving experts’ subjective judgements, Hebbian learning algor ithm has been used.