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Toplam kayıt 18, listelenen: 1-10
Multiclass Classification of Brain Cancer with Machine Learning Algorithms
(2020)
Brain cancer is one the most important disease to be treated all around the world. Classification of brain cancer using machine learning techniques has been widely studied by researchers. Microarray gene expression data ...
A Machine Learning Based Approach to Detect Survival of Heart Failure Patients
(2020)
One of the diseases with high prevalence among the consequences of cardiovascular diseases is heart failure. Heart failure is a condition in which the muscles in the heart wall become faded and dilated, limiting the heart's ...
Prediction of Frailty Grade Using Machine Learning Models
(2022)
Nowadays, frailty is becoming a major issue for the aging population. Frailty grading is important for patient quality of life because it is a geriatric syndrome of decreased physiological reserve that leads to increased ...
Effect of Polynomial, Radial Basis, and Pearson VII Function Kernels in Support Vector Machine Algorithm for Classification of Crayfish
(2022)
Freshwater crayfish are one of the most important aquatic organisms that play a pivotal role in the aquatic food chain as well as serving as bioindicators for the aquatic ecosystem health assessment. Hemocytes, the blood ...
Diagnosis of Attention Deficit Hyperactivity Disorder with combined time and frequency features
(2020)
The aim of this study was to build a machine learning model to discriminate Attention Deficit Hyperactivity Disorder (ADHD) patients and healthy controls using information from both time and frequency analysis of Event ...
Saldırı tespit sistemlerinde genetik algoritma kullanarak nitelik seçimi ve çoklu sınıflandırıcı füzyonu
(2018)
With the improvements in information systems, intrusion detection systems (IDS) become more important. IDS can be thought as a classification problem. An important step of classification applications is feature selection ...
A Novel Deep Learning Algorithm for the Automatic Detection of High-Grade Gliomas on T2-Weighted Magnetic Resonance I mages: A Preliminary Machine Learning Study
(2020)
AIM: To propose a convolutional neural network (CNN) for the automatic detection of high-grade gliomas (HGGs) on T2-weighted magnetic resonance imaging (MRI) scans.
MATERIAL and METHODS: A total of 3580 images obtained ...
Feature selection and multiple classifier fusion using genetic algorithms in intrusion detection systems
(2018)
With the improvements in information systems, intrusion detection systems (IDS) become more important. IDS can be thought as a classification problem. An important step of classification applications is feature selection ...
Machine learning-enabled healthcare information systems in view of Industrial Information Integration Engineering
(2022)
Recent studies on Machine learning (ML) and its industrial applications report that ML-enabled systems may be at a high risk of failure or they can easily fall short of business objectives. Cutting-edge developments in ...
A novel electroencephalography based approach for Alzheimer's disease and mild cognitive impairment detection
(2021)
Background and objective: Alzheimer's disease (AD) is characterized by cognitive, behavioral and intellectual deficits. The term mild cognitive impairment (MCI) is used to describe individuals whose cognitive impairment ...