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Table representation of search results timeline featuring number of search results per year.
Year | Number of Results |
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2014 | 1 |
2015 | 1 |
2016 | 2 |
2023 | 1 |
2024 | 0 |
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Page 1
Neonatal Jaundice Detection System.
J Med Syst. 2016 Jul;40(7):166. doi: 10.1007/s10916-016-0523-4. Epub 2016 May 26.
J Med Syst. 2016.
PMID: 27229489
Neonatal jaundice is a common condition that occurs in newborn infants in the first week of life. Today, techniques used for detection are required blood samples and other clinical testing with special equipment. The aim of this study is creating a non-invasive system to c …
Neonatal jaundice is a common condition that occurs in newborn infants in the first week of life. Today, techniques used for detectio …
Gastric Cancer Regional Detection System.
Ural B, Hardalaç F, Serhatlioğlu S, İlhan MN.
Ural B, et al.
J Med Syst. 2016 Jan;40(1):31. doi: 10.1007/s10916-015-0399-8. Epub 2015 Nov 9.
J Med Syst. 2016.
PMID: 26553064
During the formation of the system, to exalt the accuracy to the maximum level, 2 main stages were followed up. First, in the system, advanced image processing methods were processed between each other and obtained data were studied. Second, in the system, FFT and Log tran …
During the formation of the system, to exalt the accuracy to the maximum level, 2 main stages were followed up. First, in the system, …
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Classification of Retinal Diseases in Optical Coherence Tomography Images Using Artificial Intelligence and Firefly Algorithm.
Özdaş MB, Uysal F, Hardalaç F.
Özdaş MB, et al.
Diagnostics (Basel). 2023 Jan 25;13(3):433. doi: 10.3390/diagnostics13030433.
Diagnostics (Basel). 2023.
PMID: 36766537
Free PMC article.
Therefore, our goal is to develop a hybrid system that provides a high accuracy value, while requiring a smaller computing load and less time to diagnose biomedical diseases such as the retinal diseases we chose for this study. For this purpose, first, retinal layer extrac …
Therefore, our goal is to develop a hybrid system that provides a high accuracy value, while requiring a smaller computing load and less tim …
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Retinal blood vessel segmentation with neural network by using gray-level co-occurrence matrix-based features.
Rahebi J, Hardalaç F.
Rahebi J, et al.
J Med Syst. 2014 Aug;38(8):85. doi: 10.1007/s10916-014-0085-2. Epub 2014 Jun 24.
J Med Syst. 2014.
PMID: 24957399
It is based on fact that the co-occurrence matrix of retina image describes the transition of intensities between neighbour pixels, indicating spatial structural information of retina image. So, we first extract the features vector based on specified characteristics of the …
It is based on fact that the co-occurrence matrix of retina image describes the transition of intensities between neighbour pixels, indicati …
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