Machine Learning Algorithms for Predicting Chronic Diseases

Furkan Bulus*, Bilal Saoud, Ibraheem Shayea, Zuleikha Syzdykova

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

Özet

Chronic diseases are the leading cause of death and disability worldwide, necessitating early detection and management to mitigate their adverse effects on health and improve quality of life. Leveraging machine learning algorithms has become a prominent approach in predicting the risk of various chronic diseases. These algorithms excel in analyzing complex datasets to identify patterns and risk factors associated with chronic conditions. This study explores the application of two different machine learning algorithms on an open-source dataset to predict the risk of chronic diseases. The outcomes of these implementations are analyzed and discussed in the final section, providing insights into their effectiveness and potential for enhancing chronic disease management.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
Sayfalar1007-1012
Sayfa sayısı6
ISBN (Elektronik)9798350384598
DOI'lar
Yayın durumuYayınlandı - 2024
Etkinlik3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024 - Hybrid, Gwalior, India
Süre: 27 Haz 202428 Haz 2024

Yayın serisi

Adı2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024

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???event.eventtypes.event.conference???3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024
Ülke/BölgeIndia
ŞehirHybrid, Gwalior
Periyot27/06/2428/06/24

Bibliyografik not

Publisher Copyright:
© 2024 IEEE.

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