Bölüm "İstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Yönetim Bilişim Sistemleri Bölümü" Makale Koleksiyonu için listeleme
Toplam kayıt 26, listelenen: 1-20
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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 ... -
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 ... -
Data augmentation based malware detection using convolutional neural networks
(PeerJ Inc., 2021)Due to advancements in malware competencies, cyber-attacks have been broadly observed in the digital world. Cyber-attacks can hit an organization hard by causing several damages such as data breach, financial loss, and ... -
Data mining applications in banking sector while preserving customer privacy
(Ital Publication, 2022)In real-life data mining applications, organizations cooperate by using each other’s data on the same data mining task for more accurate results, although they may have different security and privacy concerns. Privacy-preserving ... -
Detecting Turkish fake news via text mining to protect brand integrity
(Gazi University, 2022)Fake news has been in our lives as part of the media for years. With the recent spread of digital news platforms, it affects not only traditional media but also online media as well. Therefore, while companies seek to ... -
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 ... -
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) ... -
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 ... -
Doğal gaz tüketiminin modellenmesi: Türkiye için MARS yöntemiyle bir analiz
(Gaziantep Üniversitesi Sosyal Bilimler Enstitüsü, 2022)Bu çalışmada Türkiye’deki doğal gaz talebinin tahmin edilmesine yönelik model ortaya konması amaçlanmaktadır. Doğal gaz tüketimi bağımlı değişken olarak ele alınmış, buna bağlı olarak makroekonomik veriler, iklim koşulları, ... -
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 ... -
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 ... -
A generative model based adversarial security of deep learning and linear classifier models
(Slovene Society Informatika, 2021)In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and the autonomous car. With the rapid developments of deep learning techniques, it is critical to ... -
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 ... -
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 ... -
Intelligent early warning system for epidural acute hematomas
(International Balkan University, 2020)Epidural hematoma (EAH) is the accumulation of blood in the space between the outer membrane of the brain (dura mater) and the bone. Acute subdural and epidural hematoma appears on CT scan as a hyper-dense collection often ... -
An intelligent system for document-based banking processes
(Kahramanmaras Sutcu Imam University, 2022)Business process automation has been helping companies by eliminating mundane and repetitive tasks. Automation tools have been used in many sectors, providing high full-time employee (FTE) savings and low error rates to ... -
Lemmatizer: Akıllı Türkçe kök bulma yöntemi
(International Balkan University, 2020)Yakın zamanda Türkçe doğal dil işleme alanında çeşitli çalışmalar yapılmıştır. Bu çalışmalar, üretilen akıllı bir sistemin Türkçe soru cevaplama, yazıyı başka bir dile çevirme, yazıyı özetleme,e-postalara otomatik yanıt ... -
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 ... -
On the networks of large embeddings
(2024)We define a special network that exhibits the large embeddings in any class of similar algebras. With the aid of this network, we introduce a notion of distance that conceivably counts the minimum number of dissimilarities, ...