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Yıl 2024, Cilt: 28, 438 - 447, 01.08.2024
https://doi.org/10.55549/epstem.1523634

Öz

Kaynakça

  • Shyti, B., Stergu, A., Valera, D., & Blerina, P. (2024). Food recommendation system for a healthy liver using machine learning. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 28, 438-447.

Food Recommendation System for a Healthy Liver Using Machine Learning

Yıl 2024, Cilt: 28, 438 - 447, 01.08.2024
https://doi.org/10.55549/epstem.1523634

Öz

Nowadays, the work routine, the problems we face, make us not pay proper attention to healthy eating. As a result, people get sick. We have created through mathematical knowledge (statistics, probability, linear algebra, geometry), combining the concepts of Machine Learning (Content Based Filtering, TD IDF Vectorizer Algorithm, Conditional Independence, Count Vectorization) with Python language, a Recommendation System for all people suffering from liver. Liver is one of the most important organs of our body, because it makes 500 essential functions in the organism. But we have to be aware about the types of food that we use. Also, we must be very careful with our lifestyle and diet on foods. The aim of this article is to recommend the most appropriate foods for a healthy liver. This article will help the p

Kaynakça

  • Shyti, B., Stergu, A., Valera, D., & Blerina, P. (2024). Food recommendation system for a healthy liver using machine learning. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 28, 438-447.
Toplam 1 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yazılım Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Shyti Bederiana

Stergu Argesta

Valera Dhurata

Papajani Blerina

Erken Görünüm Tarihi 29 Temmuz 2024
Yayımlanma Tarihi 1 Ağustos 2024
Gönderilme Tarihi 7 Şubat 2024
Kabul Tarihi 17 Nisan 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 28

Kaynak Göster

APA Bederiana, S., Argesta, S., Dhurata, V., Blerina, P. (2024). Food Recommendation System for a Healthy Liver Using Machine Learning. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 28, 438-447. https://doi.org/10.55549/epstem.1523634