Halk Sağlığı Alanında Makine Öğrenimi Analizinin Kullanımı

Article Properties
Abstract
Cite
TURGUTKAYA, Kübra Ecem, and Emine Didem EVCİ KİRAZ. “Halk Sağlığı Alanında Makine Öğrenimi Analizinin Kullanımı”. Journal of Intelligent Systems: Theory and Applications, vol. 7, no. 1, 2024, pp. 27-29, https://doi.org/10.38016/jista.1374240.
TURGUTKAYA, K. E., & EVCİ KİRAZ, E. D. (2024). Halk Sağlığı Alanında Makine Öğrenimi Analizinin Kullanımı. Journal of Intelligent Systems: Theory and Applications, 7(1), 27-29. https://doi.org/10.38016/jista.1374240
TURGUTKAYA, Kübra Ecem, and Emine Didem EVCİ KİRAZ. “Halk Sağlığı Alanında Makine Öğrenimi Analizinin Kullanımı”. Journal of Intelligent Systems: Theory and Applications 7, no. 1 (2024): 27-29. https://doi.org/10.38016/jista.1374240.
TURGUTKAYA KE, EVCİ KİRAZ ED. Halk Sağlığı Alanında Makine Öğrenimi Analizinin Kullanımı. Journal of Intelligent Systems: Theory and Applications. 2024;7(1):27-9.
Refrences
Title Journal Journal Categories Citations Publication Date
Can artificial intelligence enable the government to respond more effectively to major public health emergencies? ——Taking the prevention and control of Covid-19 in China as an example Socio-Economic Planning Sciences
  • Technology: Manufactures: Production management. Operations management
  • Social Sciences: Economic theory. Demography: Economics as a science
  • Social Sciences: Commerce: Business: Personnel management. Employment management
  • Social Sciences: Commerce: Business
  • Social Sciences: Economic theory. Demography: Economics as a science
15 2022
10.1016/B978-0-12-821259-2.00022-3
A machine learning-based PET/CT model for automatic diagnosis of early-stage lung cancer

Frontiers in Oncology
  • Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
  • Medicine: Medicine (General)
  • Medicine: Internal medicine: Neoplasms. Tumors. Oncology. Including cancer and carcinogens
1 2023
Predicting three-month fasting blood glucose and glycated hemoglobin changes in patients with type 2 diabetes mellitus based on multiple machine learning algorithms

Scientific Reports
  • Medicine
  • Science
  • Science: Science (General)
2 2023
10.1017/S0033291719000151