Konu "Machine Learning" için Scopus İndeksli Yayınlar Koleksiyonu listeleme
Toplam kayıt 52, listelenen: 1-20
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Advances in quantitative analysis of astrocytes using machine learning
(Wolters Kluwer Medknow Publications, 2023)Astrocytes, a subtype of glial cells, are starshaped cells that are involved in the homeostasis and blood flow control of the central nervous system (CNS). They are known to provide structural and functional support to ... -
Approaches for early detection of glaucoma using retinal images: A performance analysis
(Springer Science and Business Media Deutschland GmbH, 2020)Sight is one of the most important senses for humans, as it allows them to see and explore their surroundings. Multiple ocular diseases damaging sight have been detected over the years such as glaucoma and diabetic ... -
Automated analysis of the EEG signals for prediction of possible effectiveness of rTMS treatment in alzheimer's patient
(Institute of Electrical and Electronics Engineers Inc., 2022)Alzheimer's disease (AD) is a progressive, chronic neurodegenerative brain disease that generally infects the elderly. The analysis of electroencephalography (EEG) signals has been commonly used for diagnosis. Repetitive ... -
Blind signal analysis
(Wiley, 2021)Blind signal analysis (BSA) plays an essential role in wireless communication when the receiver does not know most or all of the received signal parameters. This chapter provides an in-depth understanding of BSA with ... -
Centralized and decentralized ml-enabled integrated terrestrial and non-terrestrial networks
(2023)Non-terrestrial networks (NTNs) are a critical enabler of the persistent connectivity vision of sixth-generation networks, as they can service areas where terrestrial infrastructure falls short. However, the integration ... -
Classification of patients with alzheimer's disease and dementia with lewy bodies using resting EEG selected features at sensor and source levels: A proof-of-concept study
(Bentham Science, 2021)Background: Early differentiation between Alzheimer's disease (AD) and Dementia with Lewy Bodies (DLB) is important for accurate prognosis, as DLB patients typically show faster disease progression. Cortical neural networks, ... -
Comparison of machine learning classification techniques to predict implantation success in an IVF treatment cycle
(Elsevier Science Ltd, 2022)Research question: Which machine learning model predicts the implantation outcome better in an IVF cycle? What is the importance of each variable in predicting the implantation outcome in an IVF cycle?Design: Retrospective ... -
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
(Institute of Electrical and Electronics Engineers Inc., 2019)Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ... -
Data analysis in health and big data: A machine learning medical diagnosis model based on patients’ complaints
(Taylor and Francis Inc., 2021)The emergence of big data made it possible to make better predictions and discover hidden patterns which contain a load of useful information. Like other domains, health discipline is also enjoying this new data science ... -
A decision support system for detecting FIP disease in cats based on machine learning methods
(2024)Cats are close friends who live with us in all aspects of life. Many diseases endanger the quality of life of cats that live with us. One of the most dangerous is infectious peritonitis in cats, also known as FIP; which ... -
Detecting spam tweets using machine learning and effective preprocessing
(Association for Computing Machinery, Inc, 2021)Nowadays, with the rapid increase in popularity of online social networks (OSNs), these platforms are realized as ideal places for spammers. Unfortunately, these spammers can easily publish malicious content, advertise ... -
Diagnosis of Covid-19 via patient breath data using artificial intelligence
(Ital Publication, 2023)Using machine learning algorithms for the rapid diagnosis and detection of the COVID-19 pandemic and isolating the patients from crowded environments are very important to controlling the epidemic. This study aims to develop ... -
Discovering the chemical factors behind regional royal jelly differences via machine learning
(Bursa Uludag University, 2023)This study aims to discover the characteristic chemical factors for determining the region of royal jelly using machine learning. 84 samples from 13 different regions of Turkey were used for the study, and the chemical ... -
Early prediction of the severe course, survival, and ICU requirements in acute pancreatitis by artificial intelligence
(Elsevier B.V., 2023)Objective: To evaluate the success of artificial intelligence for early prediction of severe course, survival, and intensive care unit(ICU) requirement in patients with acute pancreatitis(AP).Methods: Retrospectively, 1334 ... -
An early warning system using machine learning for the detection of intracranial hematomas in the emergency trauma setting
(Turkish Neurosurgical Society, 2022)AIM: To present an early warning system (EWS) that employs a supervised machine learning algorithm for the rapid detection of extra-axial hematomas (EAHs) in an emergency trauma setting. MATERIAL and METHODS: A total of ... -
Efficacy of AI-assisted personalized microbiome modulation by diet in functional constipation: A randomized controlled trial
(MDPI, 2022)Background: Currently, medications and behavioral modifications have limited success in the treatment of functional constipation (FC). An individualized diet based on microbiome analysis may improve symptoms in FC. In the ... -
An efficient approach to predict eye diseases from symptoms using machine learning and ranker-based feature selection methods
(MDPI, 2023)The eye is generally considered to be the most important sensory organ of humans. Diseases and other degenerative conditions of the eye are therefore of great concern as they affect the function of this vital organ. With ... -
Estimating multi-dimensional sparsity level for spectrum sensing
(Institute of Electrical and Electronics Engineers Inc., 2023)Identifying spectrum opportunities is a crucial element of efficient spectrum utilization for future wireless networks. Spectrum sensing offers a convenient means for revealing such opportunities. Studies showed that usage ... -
Exploring gene expression and clinical data for identifying prostate cancer severity levels using machine learning methods
(Institute of Electrical and Electronics Engineers Inc., 2023)Prostate cancer (PCa) is the most common type of cancer in men worldwide. It is a cancer that starts in the small walnut-shaped male gland called the prostate. From the prostate, it can form a metastasis into other organs. ... -
Fuzzy classification methods based diagnosis of Parkinson’s disease from speech test cases
(Bentham Science Publishers, 2019)Background: Together with the Alzheimer’s disease, Parkinson’s disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed ...