Ara
Toplam kayıt 12, listelenen: 1-10
An early prediction and diagnosis of sepsis in intensive care units: An unsupervised machine learning model
(Mugla University, 2020)
Sepsis infection, which is one of the most important causes of death in intensive care units, is seen as a severe global health crisis. If an early diagnosis of sepsis infection cannot be made, and treatment is not started ...
Analysis waste water characteristics via data mining: A Muğla province case and external validation
(Taylor and Francis Ltd., 2019)
This study is related to the analysis of characteristic parameters of domestic wastewater samples which are collected from municipal wastewater treatment plants located in the provinces of Muğla in Turkey. Used parameters ...
Differentiating gastrointestinal stromal tumors from leiomyomas using a neural network trained on endoscopic ultrasonography images
(Karger, 2022)
Background: Endoscopic ultrasonography (EUS) is crucial to diagnose and evaluate gastrointestinal mesenchymal tumors (GIMTs). However, EUS-guided biopsy does not always differentiate gastrointestinal stromal tumors (GISTs) ...
Insights into mobile health application market via a content analysis of marketplace data with machine learning
(Public Library of Science, 2021)
Background Despite the benefits offered by an abundance of health applications promoted on app marketplaces (e.g., Google Play Store), the wide adoption of mobile health and e-health apps is yet to come. Objective This ...
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 ...
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 ...
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 ...
Use of artificial intelligence in the prediction of malignant potential of gastric gastrointestinal stromal tumors
(Springer, 2022)
Background and Aims This study aimed to investigate whether AI via a deep learning algorithm using endoscopic ultrasonography (EUS) images could predict the malignant potential of gastric gastrointestinal stromal tumors ...
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 ...