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 dil | İngilizce |
---|---|
Ana bilgisayar yayını başlığı | 2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024 |
Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
Sayfalar | 1007-1012 |
Sayfa sayısı | 6 |
ISBN (Elektronik) | 9798350384598 |
DOI'lar | |
Yayın durumu | Yayınlandı - 2024 |
Etkinlik | 3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024 - Hybrid, Gwalior, India Süre: 27 Haz 2024 → 28 Haz 2024 |
Yayın serisi
Adı | 2024 IEEE 3rd World Conference on Applied Intelligence and Computing, AIC 2024 |
---|
???event.eventtypes.event.conference???
???event.eventtypes.event.conference??? | 3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024 |
---|---|
Ülke/Bölge | India |
Şehir | Hybrid, Gwalior |
Periyot | 27/06/24 → 28/06/24 |
Bibliyografik not
Publisher Copyright:© 2024 IEEE.