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Toplam kayıt 34, listelenen: 21-30
Reliability enhancement in multi-numerology-based 5G new radio using INI-aware scheduling
(Springeropen, 2019)
Multi-numerology waveform-based 5G new radio (NR) systems offer great flexibility for different requirements of users and services. However, there is a new type of problem that is defined as inter-numerology interference ...
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 ...
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 ...
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 ...
A waveform parameter assignment framework for 6G with the role of machine learning
(IEEE-Institute of Electrical and Electronics Engineers Inc., 2020)
5G enables a wide variety of wireless communications applications and use cases. There are different requirements associated with the applications, use cases, channel structure, network and user. To meet all of the ...
Novel hybridized computational paradigms integrated with five stand-alone algorithms for clinical prediction of HCV status among patients: A data-driven technique
(MDPI, 2023)
The emergence of health informatics opens new opportunities and doors for different disease diagnoses. The current work proposed the implementation of five different stand-alone techniques coupled with four different novel ...
A survey of machine learning-based methods for COVID-19 medical image analysis
(Springer Science and Business Media Deutschland GmbH, 2023)
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December ...
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 ...
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 ...
Machine learning-based analysis of glioma grades reveals co-enrichment
(MDPI, 2022)
Gliomas develop and grow in the brain and central nervous system. Examining glioma grading processes is valuable for improving therapeutic challenges. One of the most extensive repositories storing transcriptomics data for ...