AIMC Topic: Turkey
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Investigating the impact of climate variables on the organic honey yield in Turkey using XGBoost machine learning.
Journal of the science of food and agriculture
Aug 9, 2024
BACKGROUND: The Turkish organic honey industry, a major player in the global market, faces challenges due to climate fluctuations. Understanding the influence of climate factors on honey production is vital for sustainable farming and economic stabil...
Can digital leadership transform AI anxiety and attitude in nurses?
Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
Jul 31, 2024
BACKGROUND: The lack of artificial intelligence applications in nursing education and the nursing profession in Turkey and the need for strategies for integrating artificial intelligence into the nursing profession continues. At this point, there is ...
Paediatric nurses' perspectives on artificial intelligence applications: A cross-sectional study of concerns, literacy levels and attitudes.
Journal of advanced nursing
Jul 14, 2024
AIMS: This study aimed to explore the correlation between artificial intelligence (AI) literacy, AI anxiety and AI attitudes among paediatric nurses, as well as identify the influencing factors on paediatric nurses' AI attitudes.
Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye.
Environmental science and pollution research international
Jul 11, 2024
Groundwater resources in Bitlis province and its surroundings in Türkiye's Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region's volcanic rock structure. To ...
Investigating the effect of climate factors on fig production efficiency with machine learning approach.
Journal of the science of food and agriculture
May 31, 2024
BACKGROUND: This study employs a machine learning approach to investigate the impact of climate change on fig production in Turkey. The eXtreme Gradient Boosting (XGBoost) algorithm is used to analyze production performance and climate variable data ...
A case study of using artificial neural networks to predict heavy metal pollution in Lake Iznik.
Environmental monitoring and assessment
May 29, 2024
Artificial neural networks offer a viable route in assessing and understanding the presence and concentration of heavy metals that can cause dangerous complications in the wider context of water quality prediction for the sustainability of the ecosys...
Is ChatGPT reliable and accurate in answering pharmacotherapy-related inquiries in both Turkish and English?
Currents in pharmacy teaching & learning
May 3, 2024
INTRODUCTION: Artificial intelligence (AI), particularly ChatGPT, is becoming more and more prevalent in the healthcare field for tasks such as disease diagnosis and medical record analysis. The objective of this study is to evaluate the proficiency ...
How does training given to pediatric nurses about artificial intelligence and robot nurses affect their opinions and attitude levels? A quasi-experimental study.
Journal of pediatric nursing
Apr 23, 2024
PURPOSE: This study was conducted to investigate the effect of training provided to pediatric nurses on their knowledge and attitude levels about artificial intelligence and robot nurses.
Prediction of monthly evapotranspiration by artificial neural network model development with Levenberg-Marquardt method in Elazig, Turkey.
Environmental science and pollution research international
Feb 21, 2024
The phenomenon of evapotranspiration (ET) is closely linked to the issue of water scarcity, as it involves water loss through both evaporation and plant transpiration. Accurate prediction of evapotranspiration is of utmost importance in the strategic...
Tooth numbering and classification on bitewing radiographs: an artificial intelligence pilot study.
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 20, 2024
OBJECTIVE: The aim of this study is to assess the efficacy of employing a deep learning methodology for the automated identification and enumeration of permanent teeth in bitewing radiographs. The experimental procedures and techniques employed in th...
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