Ara
Toplam kayıt 48, listelenen: 11-20
Myelin detection in fluorescence microscopy images using machine learning
(Elsevier, 2020)
Background: The myelin sheath produced by glial cells insulates the axons, and supports the function of the nervous system. Myelin sheath degeneration causes neurodegenerative disorders, such as multiple sclerosis (MS). ...
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 ...
Predicting path loss distribution of an area from satellite ımages using deep learning
(IEEE - Institute of Electrical and Electronics Engineers, Inc., 2020)
Path loss prediction is essential for network planning in any wireless communication system. For cellular networks, it is usually achieved through extensive received signal power measurements in the target area. When the ...
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 ...
How to engage consumers through effective social media use-guidelines for consumer goods companies from an emerging market
(Universidad de Talca, 2021)
This study aims to establish actionable guidelines and provide strategic insights as a means of increasing the social media effectiveness of consumer brands. Post-related factors in addition to the contextual and temporal ...
SNF-CVAE: Computational method to predict drug-disease interactions using similarity network fusion and collective variational autoencoder
(Elsevier, 2021)
Drug repositioning is an emerging approach to identify novel therapeutic potentials for approved drugs and discover therapies for previously untreatable diseases. Drug repositioning has also attracted considerable attention ...
A machine learning approach to predict creatine kinase test results
(Ital Publication, 2020)
Most of the research done in the literature are based on statistical approaches and used for deriving reference limits based on lab results. As more data are available to the researchers, ML methods are more effectively ...
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 review of computational drug repositioning: Strategies, approaches, opportunities, challenges, and directions
(BMC, 2020)
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an important role in optimizing the ...
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 ...