Software fault prediction using an RNN-based deep learning approach and ensemble machine learning techniques
E Borandag - Applied Sciences, 2023 - mdpi.com
Alongside the modern software development life cycle approaches, software testing has
gained more importance and has become an area researched actively within the software …
gained more importance and has become an area researched actively within the software …
[HTML][HTML] Artificial intelligence-based prediction of molecular and genetic markers for hepatitis C–related hepatocellular carcinoma
Background: Hepatocellular carcinoma (HCC) is the main cause of mortality from cancer
globally. This paper intends to classify public gene expression data of patients with Hepatitis …
globally. This paper intends to classify public gene expression data of patients with Hepatitis …
Random ensemble mars: model selection in multivariate adaptive regression splines using random forest approach
Multivariate Adaptive Regression Splines (MARS) is a supervised learning model in
machine learning, not obtained by an ensemble learning method. Ensemble learning …
machine learning, not obtained by an ensemble learning method. Ensemble learning …
Enerji tasarruflu bina tasarımı için isıtma ve soğutma yüklerini regresyon tabanlı makine öğrenmesi algoritmaları ile modelleme
M Peker, O Özkaraca, B Kesimal - Bilişim Teknolojileri Dergisi, 2017 - dergipark.org.tr
Günümüzde bilişim teknolojileri hemen hemen her alanda kullanılmaktadır. Enerji sektörü
de bu alanlardan birisidir. Nüfusun gün geçtikçe artmasıyla birlikte bina sayısı ve binaların …
de bu alanlardan birisidir. Nüfusun gün geçtikçe artmasıyla birlikte bina sayısı ve binaların …
Estimation of gas emission values on highways in Turkey with machine learning
Due to its geographical location, Turkey has been home to many civilizations for centuries. It
has always acted as a bridge between west and east and will continue to do so. The …
has always acted as a bridge between west and east and will continue to do so. The …
Prediction of renal cell carcinoma based on ensemble learning methods
Objective: In recent years, ensemble learning methods have gained widespread use for
early diagnosis of cancer diseases. In this study, it is aimed to establish a high-performance …
early diagnosis of cancer diseases. In this study, it is aimed to establish a high-performance …
Reviewing the Factors Affecting PISA Reading Skills by Using Random Forest and MARS Methods
The research aims to determine the factors affecting PISA 2018 reading skills using Random
Forest and MARS methods and to compare their prediction abilities. This study used the …
Forest and MARS methods and to compare their prediction abilities. This study used the …
[HTML][HTML] Predicting Duodenal Cancer Risk in Patients with Familial Adenomatous Polyposis Using Machine Learning Model
Materials and Methods: The current study was performed using expression profile data from
a series of duodenal samples from familial adenomatous polyposis patients to explore …
a series of duodenal samples from familial adenomatous polyposis patients to explore …
Artificial Intelligence Evaluation of the Utility of HALP Score and Hematological Indicators in Estimating No-Reflow After Primary Percutaneous Coronary Intervention …
R Yilmaz - International Journal of Current Medical and Biological …, 2023 - ijcmbs.com
Background: Acute Myocardial Infarction (AMI) is a leading cause of mortality globally, with
ST-segment Elevation Myocardial Infarction (STEMI) being a specific type. The study aims to …
ST-segment Elevation Myocardial Infarction (STEMI) being a specific type. The study aims to …
[PDF][PDF] Predicting the Risk of Duodenal Cancer in Patients with Familial Adenomatous Polyposis Using a Machine
S Akbulut, Z Küçükakçalı… - The Turkish Journal of …, 2023 - turkjgastroenterol.org
ABSTRACT Background/Aims: The aim of this study was to both classify data of familial
adenomatous polyposis patients with and without duodenal cancer and to identify important …
adenomatous polyposis patients with and without duodenal cancer and to identify important …