Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Huzeyfe Ayaz"'
Publikováno v:
PLoS ONE, Vol 19, Iss 11, p e0308122 (2024)
This study analyzed online public discourse on Twitter (later rebranded as X) during the COVID-19 pandemic to understand key factors associated with vaccine hesitancy by employing deep-learning techniques. Text classification analysis reveals a signi
Externí odkaz:
https://doaj.org/article/4c79098f9bda4cb4b71409e86ddd32aa
Autor:
Ali Cakmak, Huzeyfe Ayaz, Soykan Arıkan, Ali R. Ibrahimzada, Şeyda Demirkol, Dilara Sönmez, Mehmet T. Hakan, Saime T. Sürmen, Cem Horozoğlu, Mehmet B. Doğan, Özlem Küçükhüseyin, Canan Cacına, Bayram Kıran, Ümit Zeybek, Mehmet Baysan, İlhan Yaylım
Publikováno v:
Medical & Biological Engineering & Computing. 61:243-258
This study explores the machine learning-based assessment of predisposition to colorectal cancer based on single nucleotide polymorphisms (SNP). Such a computational approach may be used as a risk indicator and an auxiliary diagnosis method that comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6265a033d7eff3c20f53d823b21affe4
https://doi.org/10.1007/s11517-022-02707-9
https://doi.org/10.1007/s11517-022-02707-9
Taxonomy of living organisms gains major importance in making the study of vastly heterogeneous living things easier. In addition, various fields of applied biology (e.g., agriculture) depend on classification of living creatures. Specific fragments
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a532e6a8e254bf24f523d9ceed6d1a37
