Ahmet Bozkurt

Properties of 3D printed concrete (3DPC) containing microencapsulated phase change material (PCM)

Osman Gençel, Mehrab Nodehi, Serkan Subaşı, Abid Ustaoğlu et autres

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Neutron flux determination in a multi-channel Howitzer using foil activation and Monte Carlo simulations

Recep Bıyık, İpek Balnan, Erol Kam, Ahmet Bozkurt

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Angiography-Based Detection of Coronary Artery Stenosis Using YOLO Algorithm

Hatice Kupeli, Kerim Kürşat Çevi̇k, Ahmet Bozkurt

This study investigates the efficacy of You Only Look Once (YOLO) algorithms in detecting coronary artery stenosis from angiographic images.The dataset utilized comprises 8,325 grayscale images sourced from publicly available databases, featuring patients diagnosed with single-vessel coronary artery disease.An expert cardiologist annotated …

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Enhanced Lesion Classification Based on YOLO Architectures Using Thermal Breast Images on a Patient by Patient Basis

Kerim Kürşat Çevi̇k, Soner ÇİVİLİBAL, Ahmet Bozkurt, Emre Dandıl

Breast cancer classification using deep learning architectures plays a crucial role in assisting clinicians with early-stage diagnosis.In this study, we present a comprehensive evaluation of YOLO architectures-YOLOv2, YOLOv3, YOLOv4, and YOLOv5-for the classification of breast lesions in thermal breast images.By employing these …

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Sustainable polyurethane biocomposite foams by improved microstructure, acoustic characteristics, thermoregulation performance and reduced CO2 emission through phase change material integration

Osman Gençel, Ercan Aydoğmuş, Onur Güler, Abid Ustaoğlu et autres

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Comparison of photon interaction coefficients for tumor compositions and healthy tissues simulated by Monte Carlo

Ahmet Bozkurt, Aycan Şengül

Abstract This study compares interaction coefficients of photons (namely, mass attenuation, energy absorption and energy transfer coefficients) for some tumor tissues with simlar healthy tissues. Monte Carlo calculations were performed for adenoidcystic carcinoma, melanoma, rectal adenocarcinoma, sarcoma and squamous cell lung carcinoma. …

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Global access to technologies to support safe and effective inguinal hernia surgery: prospective, international cohort study

Maria Picciochi, Adesoji Ademuyiwa, Adewale Adisa, Anita Eseenam Agbeko et autres

Technological advancement is important to improve healthcare quality and safety, especially in surgery1. For patients with an inguinal hernia, mesh and minimally invasive surgery are the two main technologies that have improved healthcare quality and safety2,3. The use of mesh is proven …

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Investigating Thermal Neutron and Gamma Ray Shielding Properties of Al Matrix Gd2O3-and W-Doped Composites Using Monte Carlo Simulations

Yasin Gaylan, Ahmet Bozkurt

This study aimed to calculate the thermal neutron (0.0253 eV) total macroscopic cross-section and gamma-ray (1.25 MeV) linear absorption coefficient for (100-x)Al-xGd2O3 (x=5 to 50) and 100-(x+y)Al-xGd2O3+yW (x,y=5 to 50) composites using MCNP6.2 simulation code. The simulation consists of a mono-energy point …

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Access to and quality of elective care: a prospective cohort study using hernia surgery as a tracer condition in 83 countries

Aslıhan Dönmez, Aakansha Giri Goswami, Aashna Raheja, Aayush Bhadani et autres

BACKGROUND: Timely and safe elective health care facilitates return to normal activities for patients and prevents emergency admissions. Surgery is a cornerstone of elective care and relies on complex pathways. This study aimed to take a whole-system approach to evaluating access to …

Monte Carlo calculated photon interaction coefficients for several body tissues

Aycan Şengül, Ahmet Bozkurt

Absorption of energy in body tissues because of radiation interactions may induce harmful outcomes such as cancer and hereditary effects due to a variety of damages in the integrity and activity of the cells. This study presents Monte Carlo calculated $\boldsymbol{\mu} /\boldsymbol{\rho}$, …

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A mask R-CNN approach for detection and classification of brain tumours from MR images

Merve Kordemir, Kerim Kürşat Çevi̇k, Ahmet Bozkurt

This study aims to tackle the implementation of a single deep learning (DL) technique to the brain tumour recognition, segmentation and classification problem based on MR images. We propose utilising the Mask R-CNN approach along with transfer learning models on images. This …

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A personalized Monte Carlo study of tumor and critical organ doses for trans-arterial radioembolization patients

Ahmet Bozkurt, Gul Demir Toker, Metin Erkılıç

Abstract Trans-arterial radioembolization (TARE) is an intra-arterial treatment method for liver malignancies. In this procedure, the therapeutic tumor dose is significant for predicting the treatment effectiveness while the dose absorbed in an organ at risk provides an understanding of its tolerance to …

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