User profiles for Yesim Aygul
Yeşim Aygülİzmir Bakırçay Üniversitesi Verified email at bakircay.edu.tr Cited by 6 |
A Depth-First Search-Based Algorithm for the Minimization of the Largest Connected Component in Networks
Identifying critical nodes is essential as it can significantly enhance network resilience and
minimize the impact of failures or attacks. This problem finds applications in various domains, …
minimize the impact of failures or attacks. This problem finds applications in various domains, …
Predicting severity of acute appendicitis with machine learning methods: a simple and promising approach for clinicians
Backgrounds Acute Appendicitis (AA) is one of the most common surgical emergencies
worldwide. This study aims to investigate the predictive performances of 6 different Machine …
worldwide. This study aims to investigate the predictive performances of 6 different Machine …
Yanık hastalarının mortalite öngörüsünde makine öğrenimi algoritmalarının kullanılması The effect of well-known burn-related features on machine learning algorithms …
O Ugurlu, Y Aygul, M Yildirim… - Ulusal travma ve acil …, 2023 - avesis.marmara.edu.tr
BACKGROUND: Burns is one of the most common traumas worldwide. Severely injured
burn patients have an increased risk for mortality and morbidity. This study aimed to evaluate …
burn patients have an increased risk for mortality and morbidity. This study aimed to evaluate …
Distributed Detecting of Critical Nodes for Maximization of Connected Components in Wireless Multi-hop Networks
In Wireless Multi-hop Networks (WMhNs), nodes whose absence significantly weakens
network connectivity or partitions the network into disconnected components are called critical …
network connectivity or partitions the network into disconnected components are called critical …
[PDF][PDF] The effect of well-known burn-related features on machine learning algorithms in burn patients' mortality prediction
BACKGROUND: Burns is one of the most common traumas worldwide. Severely injured
burn patients have an increased risk for mortality and morbidity. This study aimed to evaluate …
burn patients have an increased risk for mortality and morbidity. This study aimed to evaluate …
Tipta uzmanlik sinavinda (tus) buyuk dil modelleri insanlardan daha mi basarili?
Y Aygul, M Olucoglu, A Alpkocak - arXiv preprint arXiv:2408.12305, 2024 - arxiv.org
The potential of artificial intelligence in medical education and assessment has been made
evident by recent developments in natural language processing and artificial intelligence. …
evident by recent developments in natural language processing and artificial intelligence. …
Prediction of Financial Time Series with Deep Learning Algorithms
Stock market index data, foreign currency, and gold have an important place in financial time
series. Therefore, value or direction of movement estimation studies on this subject attracts …
series. Therefore, value or direction of movement estimation studies on this subject attracts …
Büyük ölçekli ağlar için polinom zamanlı kritik düğüm tespiti algoritması
Ağlar, karmaşık sistemlerin modellenmesinde ve analiz edilmesinde kritik bir rol oynar; bu
nedenle ağ analizleri hem sosyal hem de teknolojik sistemlerde önemli veriler sağlar. Bu …
nedenle ağ analizleri hem sosyal hem de teknolojik sistemlerde önemli veriler sağlar. Bu …
The Processing of Backness Harmony in Turkish: An ERPs Study
M Aygüneş, Y Taşdemir - avesis.istanbul.edu.tr
… Sumru Özsoy Ahmet Konrot Aslı Altan Aslı Göksel Aslı Gürer Aygül Uçar Ayhan Aksu Koç
Aysun Kunduracı Ayşe Gürel Ayten Er Balkız Öztürk Barış Kabak Başak Ümit Bozkurt Belma …
Aysun Kunduracı Ayşe Gürel Ayten Er Balkız Öztürk Barış Kabak Başak Ümit Bozkurt Belma …
[PDF][PDF] The Effect of Well-Known Burn-related Features on Machine Learning Algorithms in Burn Patients' Mortality Prediction
Burns are one of the most common traumas worldwide. Severely injured burn patients have
an increased risk for mortality and morbidity. This study aimed to evaluate well-known risk …
an increased risk for mortality and morbidity. This study aimed to evaluate well-known risk …