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    Breast cancer classification using a constructed convolutional neural network on the basis of the histopathological images by an interactive web-based interface
    (Institute of Electrical and Electronics Engineers Inc., 2019) Arslan A.K.; Yasar S.; Colak C.
    In this study, it is aimed to develop a system that can provide clinical support to physicians in the diagnosis of breast cancer with open source access artificial intelligence based software. The proposed system was designed using an open source data set for the classification of breast cancer (benign/malignant) on the basis of the histopathological images. In this context, Keras library and convolutional neural networks from deep learning methods were used on the images obtained by staining with hematoxylin and eosin of biopsy specimens taken from breast tissues. Shiny package in the R programming language is employed to develop for the user interface. According to the experimental results obtained from the study, it was determined that the designed system gives promising predictions in the classification of breast cancer and can be used for clinical decision support in the classification of the disease. This designed system can be available at http://biostatapps.inonu.edu.tr/MKSY/ in both English and Turkish. © 2019 IEEE.
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    Classification of brain tumor types by deep learning with convolutional neural network on magnetic resonance images using a developed web-based interface
    (Institute of Electrical and Electronics Engineers Inc., 2019) Ucuzal H.; Yasar S.; Colak C.
    Automated machine learning (AutoML) algorithms developed using deep learning algorithms have been the focus of interest in many studies recently. This study aims to develop a free web-based software based on deep learning that can be utilized in the diagnosis and detection of brain tumors (Glioma/Meningioma/Pituitary) on T1-weighted magnetic resonance imaging. The Keras library, which is used in Python programming language, is utilized in the construction of the deep learning algorithm in this software. The experimental results show that this software can be used for the detection and diagnosis of three types of brain tumors. This developed web-based software can be publicly available at http://biostatapps.inonu.edu.tr/BTSY/ in both English and Turkish. © 2019 IEEE.
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    Comparison of two different Nasal Interfaces used in Non-Invasive Respiratory support in terms of Neonate comfort
    (Malawi Medical Journal, 2024) Deveci M.F.; Dag Y.S.; Alagoz M.; Yasar S.; Yayan E.H.; Gokce I.K.; Ozdemir R.
    Background Non-Invasive Ventilation (NIV) is the first choice approach in neonates with sufficient respiratory effort that require respiratory support. The type of nasal interface used in NIV affects both efficacy and patient comfort. The aim of this study is to investigate the effects of different nasal interfaces used in NIV support on neonatal patient comfort. Methods Our study evaluated patients who received NIV support for 24 hours. The patients were randomly divided into two groups according to the type of nasal interface used, which were RAM cannula and short binasal prong (SBP). The patients’ demographic and clinical data were noted. Their sleep was monitored for 24 hours with an actigraphy device. Results A total of 82 patients were evaluated. The sleep efficiency in the RAM cannula group was significantly higher (respectively, 65.7% [10.22-95.25] vs. 57.81% [2.49-77], p=0.004). Although not statistically significant, the neonates in the RAM cannula group exhibited longer total sleep time (respectively, 10.4 ± 4.28 hours vs. 9.02 ± 3.73 hours, p=0.161). Comparison of heart rates and respiratory rates indicate that the patients in the RAM cannula group were more comfortable. Conclusions Our study found that infants who received NIV support through a RAM cannula experienced more efficient sleep. Holistic approaches in neonatal intensive care units are vital for better neurodevelopmental outcomes in newborns. Although non-invasive, the interface used in NIV should also be a part of this holistic approach. © 2024 Kamuzu University of Health Sciences.
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    High Voltage Ga-Doped P2-Type Na2/3Ni0.2Mn0.8O2 Cathode for Sodium-Ion Batteries
    (John Wiley and Sons Inc, 2024) Liu H.; Hong N.; Bugday N.; Yasar S.; Altin S.; Deng W.; Deng W.
    Ni/Mn-based oxide cathode materials have drawn great attention due to their high discharge voltage and large capacity, but structural instability at high potential causes rapid capacity decay. How to moderate the capacity loss while maintaining the advantages of high discharge voltage remains challenging. Herein, the replacement of Mn ions by Ga ions is proposed in the P2-Na2/3Ni0.2Mn0.8O2 cathode for improving their cycling performances without sacrificing the high discharge voltage. With the introduction of Ga ions, the relative movement between the transition metal ions is restricted and more Na ions are retained in the lattice at high voltage, leading to an enhanced redox activity of Ni ions, validated by ex situ synchrotron X-ray absorption spectrum and X-ray photoelectron spectroscopy. Additionally, the P2-O2 phase transition is replaced by a P2-OP4 phase transition with a smaller volume change, reducing the lattice strain in the c-axis direction, as detected by operando/ex situ X-ray diffraction. Consequently, the Na2/3Ni0.21Mn0.74Ga0.05O2 electrode exhibits a high discharge voltage close to that of the undoped materials, while increasing voltage retention from 79% to 93% after 50 cycles. This work offers a new avenue for designing high-energy density Ni/Mn-based oxide cathodes for sodium-ion batteries. © 2023 Wiley-VCH GmbH.
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    Open-Source Web-Based Software for Performing Permutation Tests
    (Institute of Electrical and Electronics Engineers Inc., 2019) Tunc Z.; Yasar S.; Colak C.
    In this study, it is aimed to develop a new user-friendly web-based software which can overcome the difficulties of use due to the limitations in the use stages of parametric and non-parametric tests and can easily use the permutation tests which can be used as an alternative to these tests.Shiny, an open-source R package, is used to develop the recommended web software. In the developed software, by selecting the Specify Sample Number tab, the number of samples presented as Single, Two and More than two options is selected and analyzes are made by selecting the appropriate data set from the file upload menu.In this study, in order to show the way the software works and to evaluate its outputs, a data set containing 1000 observations with the standard normal distribution of variables consisting of two variables was used. Two Dependent Sample Permutation Tests were selected to analyze whether there was any difference between the variables. According to the results, no statistically significant difference was found between the variables.The developed software is a new user-friendly web-based software that can be used to perform the permutation tests in an easy way as an alternative to parametric and non-parametric tests. © 2019 IEEE.