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Mutlu Mete

Showing results (11-20 of 34) with videos related to

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Bioinformatics (Oxford, England)|June 10, 2010
A soft kinetic data structure for lesion border detectionSinan Kockara, Mutlu Mete, Vincent Yip, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|March 26, 2015
GPU accelerated dynamic functional connectivity analysis for functional MRI dataDevrim Akgün, Ünal Sakoğlu, Johnny Esquivel, et al.
Bioengineering (Basel, Switzerland)|June 26, 2026
Validation-Aware Retrospective EEG Treatment-Response Modelling Using Chaotic Pattern of Prime Numbers Features: Segment-Level Separability and Subject-Wise GeneralisationHesam Akbari, Mutlu Mete, Reza Rostami, et al.
Journal of Neuroscience Research|April 9, 2019
Classification of cocaine-dependent participants with dynamic functional connectivity from functional magnetic resonance imaging dataUnal Sakoglu, Mutlu Mete, John Esquivel, et al.
BMC Bioinformatics|March 16, 2019
Local edge-enhanced active contour for accurate skin lesion border detectionMustafa Bayraktar, Sinan Kockara, Tansel Halic, et al.
International Journal of Laboratory Hematology|December 19, 2024
Absolute Immature Platelet Count: An Accessible Biomarker to Distinguish Aplastic Anemia and Immune ThrombocytopeniaMichelle Zhu, Prajwal Sharma, Mutlu Mete, et al.
BMC Bioinformatics|October 22, 2016
Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approachMutlu Mete, Unal Sakoglu, Jeffrey S Spence, et al.
BMC Bioinformatics|October 22, 2016
Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy imagesSertan Kaya, Mustafa Bayraktar, Sinan Kockara, et al.
Psychiatry Research. Neuroimaging|June 16, 2026
Explainable EEG-based prediction of depression therapy outcomes using local Fibonacci pattern analysisHesam Akbari, Zhenni Liang, Narges Nasehi Najafabadi, et al.
Brain Sciences|March 27, 2026
Towards the Development of a Deep Learning Framework Using Adaptive and Non-Adaptive Time-Frequency Features for EEG-Based Depression Therapy PredictionHesam Akbari, Sara Bagherzadeh, Javid Farhadi Sedehi, et al.
Pageof 4

Showing results (11-20 of 34) with videos related to

Sort By:
Pageof 4
Bioinformatics (Oxford, England)|June 10, 2010
A soft kinetic data structure for lesion border detectionSinan Kockara, Mutlu Mete, Vincent Yip, et al.
Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society|March 26, 2015
GPU accelerated dynamic functional connectivity analysis for functional MRI dataDevrim Akgün, Ünal Sakoğlu, Johnny Esquivel, et al.
Bioengineering (Basel, Switzerland)|June 26, 2026
Validation-Aware Retrospective EEG Treatment-Response Modelling Using Chaotic Pattern of Prime Numbers Features: Segment-Level Separability and Subject-Wise GeneralisationHesam Akbari, Mutlu Mete, Reza Rostami, et al.
Journal of Neuroscience Research|April 9, 2019
Classification of cocaine-dependent participants with dynamic functional connectivity from functional magnetic resonance imaging dataUnal Sakoglu, Mutlu Mete, John Esquivel, et al.
BMC Bioinformatics|March 16, 2019
Local edge-enhanced active contour for accurate skin lesion border detectionMustafa Bayraktar, Sinan Kockara, Tansel Halic, et al.
International Journal of Laboratory Hematology|December 19, 2024
Absolute Immature Platelet Count: An Accessible Biomarker to Distinguish Aplastic Anemia and Immune ThrombocytopeniaMichelle Zhu, Prajwal Sharma, Mutlu Mete, et al.
BMC Bioinformatics|October 22, 2016
Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approachMutlu Mete, Unal Sakoglu, Jeffrey S Spence, et al.
BMC Bioinformatics|October 22, 2016
Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy imagesSertan Kaya, Mustafa Bayraktar, Sinan Kockara, et al.
Psychiatry Research. Neuroimaging|June 16, 2026
Explainable EEG-based prediction of depression therapy outcomes using local Fibonacci pattern analysisHesam Akbari, Zhenni Liang, Narges Nasehi Najafabadi, et al.
Brain Sciences|March 27, 2026
Towards the Development of a Deep Learning Framework Using Adaptive and Non-Adaptive Time-Frequency Features for EEG-Based Depression Therapy PredictionHesam Akbari, Sara Bagherzadeh, Javid Farhadi Sedehi, et al.
Pageof 4