Konu "Machine learning" için Fakülteler listeleme
Toplam kayıt 17, listelenen: 1-17
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Classification of new titles by two stage latent dirichlet allocation
(Ieee, 2018)With the rapid development of the Internet, thousands of different news reports from different channels are presented to us. So much news, particularly in the media sector, is an important question to be categorized and ... -
Comparison of mandibular morphometric parameters in digital panoramic radiography in gender determination using machine learning
(Springer, 2024)Objective: This study aimed to evaluate the usability of morphometric features obtained from mandibular panoramic radiographs in gender determination using machine learning algorithms. Materials and methods: High-resolution ... -
A data-driven Bayesian Network model for oil spill occurrence prediction using tankship accidents
(Elsevier, 2022)Oil spills are one of the most important issues facing the maritime industry, with a wide range of catastrophic environmental, social, and economic effects. While all marine accidents can cause pollution, tankships are ... -
A data-driven predictive maintenance model to estimate RUL in a multi-rotor UAS
(Sage Publications, 2023)Unmanned Aircraft Systems (UAS) has become widespread over the last decade in various commercial or personal applications such as entertainment, transportation, search and rescue. However, this emerging growth has led to ... -
Determination of growth and developmental stages in hand–wrist radiographs: Can fractal analysis in combination with artificial intelligence be used?
(Springer, 2024)Purpose: The goal of this work was to assess the classification of maturation stage using artificial intelligence (AI) classifiers. Methods: Hand–wrist radiographs (HWRs) from 1067 individuals aged between 7 and 18 years ... -
Early diagnosis of diabetes mellitus by machine learning methods according to plasma glucose concentration, serum ınsulin resistance and diastolic blood pressure ındicators
(Effect Publishing Agency ( EPA ), 2022)Aim: It is a known fact that diabetes mellitus is increasing frequently and triggering many different diseases. Therefore, early diagnosis of the disease is important. This study was trying to predict the early diagnosis ... -
An investigation of ensemble learning methods in classification problems and an application on non-small-cell lung cancer data
(Effect Publishing Agency ( EPA ), 2022)This study aims to classify NSCLC death status and consists of patient records of 24 variables created by the open-source dataset of the cancer data site. Besides, basic classifiers such as SMO (Sequential Minimal ... -
Machine learning based feature optimization and early detection system in heart diseases
(IEEE, 2023)In today's world, humanity faces a myriad of challenges, many of which pose significant threats to our well-being. Chief among these challenges are health-related issues. Among these health problems, heart diseases stand ... -
Machine learning driven optimization and parameter selection of multi-surface HTS Maglev
(Elsevier, 2024)This research aims to tackle the challenges posed by precise force measurement for high temperature superconducting (HTS) Maglev systems, including mechanical constraints, step motor limitations, and sensor resolutions. ... -
Machine learning models to estimate the elastic modulus of weathered magmatic rocks
(Springer, 2021)In recent years, several soft computing models have been proposed to estimate the elastic modulus of magmatic rocks. However, there are lacks in models that consider the different weathering degrees in determining the ... -
Makine öğrenmesi yoluyla sendikal haklarla ilgili olarak anayasa mahkemesine yapılan bireysel başvuruların analizi
(Anayasa Hukuku Araştırmaları Derneği, 2021)Bu çalışma bir yapay zekâ tekniği olan makine öğrenmesi yoluyla Anayasa Mahkemesinin (AYM) sendikal haklarla ilgili bireysel başvuru kararlarının ihlalle sonuçlanıp sonuçlanmadığını öngörmeyi amaçlamaktadır. Konunun ... -
A method to classify steel plate faults based on ensemble learning
(2022)With the industrial revolution 4.0, machine learning methods are widely used in all aspects of manufacturing to perform quality prediction, fault diagnosis, or maintenance. In the steel industry, it is important to ... -
Non-compliance of the European Court of Human Rights decisions: A machine learning analysis
(Elsevier, 2023)The paper investigates all (971) non-executed pending leading cases of the European Court of Human Rights (ECtHR) between 2012 and 2020 through Machine Learning (ML) techniques. Drawing on the extant scholarship, our ... -
A novel framework for strength prediction of geopolymer mortar: Renovative precursor effect
(Elsevier, 2023)Concrete is the most used building material today as it has many advantages due to its structure. Geopolymer composites could potentially replace concrete in the future due to the demands of the construction industry. The ... -
Preoperative assessment of grade, T stage, and lymph node involvement: machine learning-based CT texture analysis in colon cancer
(Springer, 2023)Purpose To investigate whether texture analysis of primary colonic mass in preoperative abdominal computed tomography (CT) scans of patients diagnosed with colon cancer could predict tumor grade, T stage, and lymph node ... -
Radiomics-based machine learning in the differentiation of benign and malignant bowel wall thickening radiomics in bowel wall thickening
(Springer, 2024)PurposeTo distinguish malignant and benign bowel wall thickening (BWT) by using computed tomography (CT) texture features based on machine learning (ML) models and to compare its success with the clinical model and combined ... -
Stacked ensemble modeling for improved tuberculosis treatment outcome prediction in pediatric cases
(Wiley, 2024)The promising results of ML (machine learning) methods in various disciplines have led to the frequent use of these methods in health fields such as disease diagnosis, personalized medicine, medical image-based diagnosis, ...