Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Ceyda Turan Bektas"'
Autor:
Aytul Hande Yardimci, Burak Kocak, Ipek Sel, Hasan Bulut, Ceyda Turan Bektas, Merve Cin, Nevra Dursun, Hasan Bektas, Ozlem Mermut, Veysi Hakan Yardimci, Ozgur Kilickesmez
Publikováno v:
Japanese Journal of Radiology. 41:71-82
Variable response to neoadjuvant chemoradiotherapy (nCRT) is observed among individuals with locally advanced rectal cancer (LARC), having a significant impact on patient management. In this work, we aimed to investigate the potential value of machin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ffab7b6b3af83ebd818d9c8d5d35a4d6
https://doi.org/10.1007/s11604-022-01325-7
https://doi.org/10.1007/s11604-022-01325-7
Publikováno v:
İstanbul Medical Journal, Vol 22, Iss 3, Pp 192-196 (2021)
Introduction:To explore the role of computed tomography (CT) texture analysis in predicting T-stage of gastric cancers (GC).Methods:Preoperative enhanced CT images of 110 patients (men: 84, women: 26) with GC were reviewed retrospectively. Regions of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ed34aea890bc6740fbce9afecc4d3ad0
https://doaj.org/article/e61ea8b6c8124d3e8c534eb4e52ac00e
https://doaj.org/article/e61ea8b6c8124d3e8c534eb4e52ac00e
Publikováno v:
American Journal of Roentgenology. 215:920-928
OBJECTIVE. The purpose of this study is to provide an overview of the traditional machine learning (ML)-based and deep learning-based radiomic approaches, with focus placed on renal mass characterization. CONCLUSION. ML currently has a very low barri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c13ea386d53c27d4e4d99d312494d855
https://doi.org/10.2214/ajr.19.22608
https://doi.org/10.2214/ajr.19.22608
Autor:
Hale Demir, Cagri Erdim, Ozgur Kilickesmez, Sevim Baykal Koca, Ceyda Turan Bektas, Aytul Hande Yardimci, Burak Kocak
Publikováno v:
Academic Radiology. 27:1422-1429
Rationale and Objectives This study aimed to investigate whether benign and malignant renal solid masses could be distinguished through machine learning (ML)-based computed tomography (CT) texture analysis. Materials and Methods Seventy-nine patients
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::223e5bca73f68de428999cfff85361bd
https://doi.org/10.1016/j.acra.2019.12.015
https://doi.org/10.1016/j.acra.2019.12.015
Publikováno v:
İstanbul Medical Journal, Vol 20, Iss 6, Pp 547-552 (2019)
Introduction:The purpose of this study is to provide a classification of different types of hepatic hydatid cysts by measuring the mean apparent diffusion coefficient (ADC) and exponential apparent diffusion coefficient (EADC) using diffusion-weighte
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c6a9bfe16aa47464cd6816b2f3fec9e1
https://doi.org/10.4274/imj.galenos.2019.98958
https://doi.org/10.4274/imj.galenos.2019.98958
Autor:
Mahmut Gokhan Toktas, Nejdet Karsiyakali, Ceyda Turan Bektas, Ugur Yucetas, Huseyin Aytac Ates, Sevim Baykal Koca
Publikováno v:
Journal of Urological Surgery, Vol 6, Iss 2, Pp 148-151 (2019)
Cystic nephroma is a rare benign tumour of the kidney. The symptoms are often non-specific and the diagnosis of the disease is usually made incidentally. Definitive diagnosis can be possible with histopathological evaluation. Surgical resection provi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::10b2f750e57c53c640412f4a6d8db4c2
https://doi.org/10.4274/jus.galenos.2018.2190
https://doi.org/10.4274/jus.galenos.2018.2190
Autor:
Aytul Hande Yardimci, Hasan Bektas, Cigdem Usul Afsar, Burak Kocak, Ipek Sel, Ozgur Kilickesmez, Ceyda Turan Bektas, Rıza Umar Gürsu, Enver Yarikkaya, Nevra Dursun
Publikováno v:
Diagn Interv Radiol
Purpose Lymphovascular invasion (LVI) and perineural invasion (PNI) are associated with poor prognosis in gastric cancers. In this work, we aimed to investigate the potential role of computed tomography (CT) texture analysis in predicting LVI and PNI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::548a2810d4d6f2047955358f0285a119
https://europepmc.org/articles/PMC7664741/
https://europepmc.org/articles/PMC7664741/
Autor:
Mehmet Hamza Turkcanoglu, Sevim Baykal Koca, Aytul Hande Yardimci, Burak Kocak, Ozgur Kilickesmez, Ugur Yucetas, Ceyda Turan Bektas, Cagri Erdim
Publikováno v:
European Radiology. 29:1153-1163
To evaluate the performance of quantitative computed tomography (CT) texture analysis using different machine learning (ML) classifiers for discriminating low and high nuclear grade clear cell renal cell carcinomas (cc-RCCs). This retrospective study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f61c8f5b7df3b8f714c2f3c16fdd5559
https://doi.org/10.1007/s00330-018-5698-2
https://doi.org/10.1007/s00330-018-5698-2
Autor:
Enver Yarikkaya, Aytul Hande Yardimci, Rıza Umar Gürsu, Hasan Bektaş, Elif Ertas, Veysi Hakan Yardimci, Nevra Dursun, Cigdem Usul Afsar, Ipek Sel, Ozgur Kilickesmez, Ceyda Turan Bektas
Publikováno v:
Japanese journal of radiology. 38(6)
The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative perio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0ce186151d24a65e58f658cd87efe78e
https://pubmed.ncbi.nlm.nih.gov/32140880
https://pubmed.ncbi.nlm.nih.gov/32140880
Autor:
Aytul Hande Yardimci, Sevim Baykal Koca, Cagri Erdim, Ozgur Kilickesmez, Ceyda Turan Bektas, Burak Kocak, Mehmet Hamza Turkcanoglu, Ugur Yucetas
Publikováno v:
European journal of radiology. 107
Objective To develop externally validated, reproducible, and generalizable models for distinguishing three major subtypes of renal cell carcinomas (RCCs) using machine learning-based quantitative computed tomography (CT) texture analysis (qCT-TA). Ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::244ce22ebd37b3022ed1548c630c6d7c
https://pubmed.ncbi.nlm.nih.gov/30292260
https://pubmed.ncbi.nlm.nih.gov/30292260