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2. Generating Realistic Counterfactuals for Retinal Fundus and OCT Images using Diffusion Models

Author

Ilanchezian, Indu, Boreiko, Valentyn, Kühlewein, Laura, Huang, Ziwei, Ayhan, Murat Seçkin, Hein, Matthias, Koch, Lisa, and Berens, Philipp

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Counterfactual reasoning is often used in clinical settings to explain decisions or weigh alternatives. Therefore, for imaging based specialties such as ophthalmology, it would be beneficial to be able to create counterfactual images, illustrating answers to questions like "If the subject had had diabetic retinopathy, how would the fundus image have looked?". Here, we demonstrate that using a diffusion model in combination with an adversarially robust classifier trained on retinal disease classification tasks enables the generation of highly realistic counterfactuals of retinal fundus images and optical coherence tomography (OCT) B-scans. The key to the realism of counterfactuals is that these classifiers encode salient features indicative for each disease class and can steer the diffusion model to depict disease signs or remove disease-related lesions in a realistic way. In a user study, domain experts also found the counterfactuals generated using our method significantly more realistic than counterfactuals generated from a previous method, and even indistinguishable from real images.

Published
2023

5. The percentage of ALK-positive cells and the efficacy of first-line alectinib in advanced non-small cell lung cancer: is it a novel factor for stratification? (Turkish Oncology Group Study)

Author

Hizal, Mutlu, Bilgin, Burak, Paksoy, Nail, Atcı, Muhammed Mustafa, Kahraman, Seda, Kılıçkap, Saadettin, Güven, Deniz Can, Keskinkılıç, Merve, Ayhan, Murat, Eren, Önder, Mustafayev, Fatma Nihan Akkoç, Yaman, Şebnem, Bayram, Ertuğrul, Ertürk, İsmail, Özcan, Erkan, Korkmaz, Mustafa, Akagündüz, Baran, Erdem, Dilek, Telli, Tuğba Akın, Aksoy, Asude, Üskent, Necdet, Baytemür, Naziyet Köse, Gülmez, Ahmet, Aydın, Dinçer, Şakalar, Teoman, Arak, Hacı, Tatlı, Ali Murat, Ergün, Yakup, Ak, Naziye, Ünal, Çağlar, Özgün, Mehmet Alpaslan, Yalçın, Bülent, Öztop, İlhan, Algın, Efnan, Sakin, Abdullah, Aydıner, Adnan, Yumuk, Perran Fulden, and Şendur, Mehmet Ali Nahit

Published
2023
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6. Visual Explanations for the Detection of Diabetic Retinopathy from Retinal Fundus Images

Author

Boreiko, Valentyn, Ilanchezian, Indu, Ayhan, Murat Seçkin, Müller, Sarah, Koch, Lisa M., Faber, Hanna, Berens, Philipp, Hein, Matthias, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Wang, Linwei, editor, Dou, Qi, editor, Fletcher, P. Thomas, editor, Speidel, Stefanie, editor, and Li, Shuo, editor

Published
2022
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7. The real-life efficacy and safety of osimertinib in pretreated advanced non-small cell lung cancer patients with T790M mutation: a Turkish Oncology Group Study

Author

Hizal, Mutlu, Bilgin, Burak, Paksoy, Nail, Açıkgöz, Özgür, Sezer, Ahmet, Gürbüz, Mustafa, Ak, Naziye, Yücel, Şebnem, Ayhan, Murat, Erol, Cihan, Demirkıran, Aykut, Mandel, Nil Molinas, Shbair, Abdallah, Gökmen, İvo, Başoğlu, Tuğba, Paydaş, Semra, Demiray, Atike Gökçen, İriağaç, Yakup, Şakalar, Teoman, Zeynelgil, Esra, Tatlı, Ali Murat, Bahçeci, Aykut, Güven, Deniz Can, Caner, Burcu, Can, Alper, Gülmez, Ahmet, Karakaş, Yusuf, Yalçın, Bülent, Demirkazık, Ahmet, Bilici, Ahmet, Aydıner, Adnan, Yumuk, Perran Fulden, and Şendur, Mehmet Ali Nahit

Published
2022
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8. Multiple Kernel Learning and Automatic Subspace Relevance Determination for High-dimensional Neuroimaging Data

Author

Ayhan, Murat Seckin, Raghavan, Vijay, and Initiative, Alzheimer's disease Neuroimaging

Subjects
Computer Science - Learning, Quantitative Biology - Neurons and Cognition, Statistics - Machine Learning
Abstract

Alzheimer's disease is a major cause of dementia. Its diagnosis requires accurate biomarkers that are sensitive to disease stages. In this respect, we regard probabilistic classification as a method of designing a probabilistic biomarker for disease staging. Probabilistic biomarkers naturally support the interpretation of decisions and evaluation of uncertainty associated with them. In this paper, we obtain probabilistic biomarkers via Gaussian Processes. Gaussian Processes enable probabilistic kernel machines that offer flexible means to accomplish Multiple Kernel Learning. Exploiting this flexibility, we propose a new variation of Automatic Relevance Determination and tackle the challenges of high dimensionality through multiple kernels. Our research results demonstrate that the Gaussian Process models are competitive with or better than the well-known Support Vector Machine in terms of classification performance even in the cases of single kernel learning. Extending the basic scheme towards the Multiple Kernel Learning, we improve the efficacy of the Gaussian Process models and their interpretability in terms of the known anatomical correlates of the disease. For instance, the disease pathology starts in and around the hippocampus and entorhinal cortex. Through the use of Gaussian Processes and Multiple Kernel Learning, we have automatically and efficiently determined those portions of neuroimaging data. In addition to their interpretability, our Gaussian Process models are competitive with recent deep learning solutions under similar settings., Comment: The material presented here is to promote the dissemination of scholarly and technical work in a timely fashion. Data in this article are from ADNI (adni.loni.usc.edu). As such, ADNI provided data but did not participate in writing of this report

Published
2017

9. The prognostic factors in patients with advanced hepatocellular carcinoma: impact of treatment sequencing.

Author

Köstek, Osman, Demirel, Ahmet, Hacıoğlu, Muhammet Bekir, Tastekin, Didem, Karabulut, Senem, Gündogdu, Abidin, Sever, Nadiye, Ayhan, Murat, Çelebi, Abdussamed, Majidova, Nargiz, Yaşar, Alper, Ağyol, Yeşim, Erel, Pınar, Kocaaslan, Erkam, Güren, Ali Kaan, Arıkan, Rukiye, Isık, Selver, Ercelep, Ozlem, Goksu, Sema Sezgin, and Alandag, Celal

Published
2024
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11. Interpretable Gender Classification from Retinal Fundus Images Using BagNets

Author

Ilanchezian, Indu, Kobak, Dmitry, Faber, Hanna, Ziemssen, Focke, Berens, Philipp, Ayhan, Murat Seçkin, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, de Bruijne, Marleen, editor, Cattin, Philippe C., editor, Cotin, Stéphane, editor, Padoy, Nicolas, editor, Speidel, Stefanie, editor, Zheng, Yefeng, editor, and Essert, Caroline, editor

Published
2021
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13. Real-life comparison of the afatinib and first-generation tyrosine kinase inhibitors in nonsmall cell lung cancer harboring EGFR exon 19 deletion: a Turk Oncology Group (TOG) study

Author

Bilgin, Burak, Sendur, Mehmet Ali Nahit, Yucel, Sebnem, Celik, Emir, Ozyukseler, Deniz Tataroglu, Ayhan, Murat, Basoglu, Tugba, Ilhan, Aysegul, Akdeniz, Nadiye, Gulmez, Ahmet, Dogan, Izzet, Aktas, Burak Yasin, Gurbuz, Mustafa, Koca, Sinan, Paydas, Semra, Tatli, Ali Murat, Cinkir, Havva Yesil, Alan, Ozkan, Erol, Cihan, Hizal, Mutlu, Kut, Engin, Menevse, Serkan, Sakalar, Teoman, Taskaynatan, Halil, Deniz, Gulhan Ipek, Karaagac, Mustafa, Avci, Okan, Sen, Erdem, Karatas, Fatih, Akinci, Muhammed Bulent, Dede, Didem Sener, Demir, Atakan, Demirkazık, Ahmet, Oksuzoglu, Berna, Kilickap, Sadettin, Yumuk, Fulden, and Yalcin, Bulent

Published
2021
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16. Efficacy and safety of bevacizumab in patients with low-grade serous ovarian cancer

Author

Karacin, Cengiz, primary, Sunar, Veli, additional, Urakci, Zuhat, additional, Yilmaz, Ali, additional, Ayhan, Murat, additional, Ersoy, Mustafa, additional, Guven, Deniz Can, additional, Erturk, Ismail, additional, Durmus, Yasin, additional, Karacin, Pinar, additional, Boran, Nurettin, additional, Ustun, Yaprak Engin, additional, Meydan, Mutlu, additional, Dogan, Mutlu, additional, Oksuzoğlu, Berna, additional, Ates, Ozturk, additional, Karaca, Mustafa, additional, Uncu, Dogan, additional, Ergun, Yakup, additional, and Arik, Zafer, additional

Published
2024
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19. Efficient and Automatic Subspace Relevance Determination via Multiple Kernel Learning for High-Dimensional Neuroimaging Data

Author

Ayhan, Murat Seçkin, Raghavan, Vijay, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Wang, Shouyi, editor, Yamamoto, Vicky, editor, Su, Jianzhong, editor, Yang, Yang, editor, Jones, Erick, editor, Iasemidis, Leon, editor, and Mitchell, Tom, editor

Published
2018
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20. The real‐world outcomes of Lutetium‐177 PSMA‐617 radioligand therapy in metastatic castration‐resistant prostate cancer: Turkish Oncology Group multicenter study

Author

Almuradova, Elvina, primary, Seyyar, Mustafa, additional, Arak, Hacı, additional, Tamer, Fatih, additional, Kefeli, Umut, additional, Koca, Sinan, additional, Sen, Erdem, additional, Telli, Tugba Akin, additional, Karatas, Fatih, additional, Gokmen, Ivo, additional, Turhal, Nazım Serdar, additional, Sakalar, Teoman, additional, Ayhan, Murat, additional, Ekinci, Ferhat, additional, Hafizoglu, Emre, additional, Kahraman, Seda, additional, Kesen, Oguzhan, additional, Unal, Caglar, additional, Alan, Ozkan, additional, Celik, Serdar, additional, Yekeduz, Emre, additional, Omur, Ozgür, additional, and Gokmen, Erhan, additional

Published
2023
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21. The Effectiveness of Adjuvant PD-1 Inhibitors in Patients With Surgically Resected Stage III/IV Acral Melanoma

Author

Arak, Haci, Erkiliç, Suna, Yaslikaya, Şendağ, Eylemer Mocan, Eda, Aktaş, Gökmen, Özdemir, Melek, Semiz, Hüseyin Salih, kiliçkap, Saadettin, Özalp, Faruk Recep, Sever, Özlem Nuray, Akdağ, Goncagül, Ağaoğlu, Ahmet Burak, Özçelik, Melike, Sari, Murat, Arcagök, Murat, Anik, Hicran, Yayla, Şaziye Burçak, Sever, Nadiye, Açar, Fatma Pinar, Bayrakçi, İsmail, Turhal, Serdar, Ayhan, Murat, and Kuş, Tülay

Abstract

Our aim was to assess the efficacy of adjuvant programmed cell death protein-1 (PD-1) inhibitors and compare the other adjuvant treatments in patients with surgically resected stage III or IV acral melanoma. This study is a multicenter, retrospective analysis. We included 114 patients with stage III or IV acral malignant melanoma who underwent surgery within the past 10 years. We analyzed the effect of adjuvant programmed cell death protein-1 inhibitors on disease-free survival (DFS). The mean follow-up was 40 months, during which 69 (59.5%) patients experienced recurrence. Among the participants, 64 (56.1%) received systemic adjuvant therapy. Specifically, 48.4% received anti–PD-1 therapy, 29.7% received interferon, 14.1% received tezozolomide, and 7.8% received B-Raf proto-oncogene/mitogen-activated protein kinase inhibitors. Patients who received adjuvant therapy had a median DFS of 24 (10.9–37.2) months, whereas those who did not receive adjuvant therapy had a median DFS of 15 (9.8–20.2) months. Multivariate analysis for DFS revealed that the receipt of adjuvant therapy and lymph node metastasis stage were independent significant parameters (P= 0.021, P= 0.018, respectively). No statistically significant difference was observed for DFS between programmed cell death protein-1 inhibitor treatment and other adjuvant treatments. Regarding overall survival (OS), patients who received adjuvant treatment had a median OS of 71 (30.4–111.7) months, whereas those who did not receive adjuvant treatment had a median OS of 38 (16.7–59.3; P= 0.023) months. In addition, there were no significant differences in OS observed between various adjuvant treatment agents (P= 0.122). In our study, we have shown that adjuvant therapy had a positive effect on both DFS and OS in patients with stages III–IV acral melanoma who underwent curative intent surgery. Notably, we found no significant differences between anti–PD-1 therapy and other adjuvant therapies.

Published
2024
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22. The real‐world outcomes of Lutetium‐177 PSMA‐617 radioligand therapy in metastatic castration‐resistant prostate cancer: Turkish Oncology Group multicenter study.

Author

Almuradova, Elvina, Seyyar, Mustafa, Arak, Hacı, Tamer, Fatih, Kefeli, Umut, Koca, Sinan, Sen, Erdem, Telli, Tugba Akin, Karatas, Fatih, Gokmen, Ivo, Turhal, Nazım Serdar, Sakalar, Teoman, Ayhan, Murat, Ekinci, Ferhat, Hafizoglu, Emre, Kahraman, Seda, Kesen, Oguzhan, Unal, Caglar, Alan, Ozkan, and Celik, Serdar

Subjects
CASTRATION-resistant prostate cancer, ANDROGEN receptors, PROSTATE-specific antigen
Abstract

Metastatic castration‐resistant prostate cancer (mCRPC) remains a challenging condition to treat despite recent advancements. This retrospective study aimed to assess the activity and tolerability of Lutetium‐177 (Lu‐177) PSMA‐617 radioligand therapy (RLT) in mCRPC patients across multiple cancer centers in Turkey. The study included 165 patients who received at least one cycle of Lu‐177 PSMA‐617 RLT, with the majority having bone metastases and undergone prior treatments. Prostate‐specific antigen (PSA) levels were assessed before each treatment cycle, and the biochemical response was evaluated in accordance with the Prostate Cancer Work Group 3 Criteria. The PSA decline of ≥50% was classified as a response, while an increase of ≥25% in PSA levels was indicative of progressive disease. Neither response nor progression was considered as stable disease. The Lu‐177 PSMA‐617 RLT led to a significant PSA response, with 50.6% of patients achieving a >50% decrease in PSA levels. Median overall survival (OS) and progression‐free survival were 13.5 and 8.2 months, respectively. Patients receiving Lu‐177 PSMA‐617 RLT in combination with androgen receptor pathway inhibitors (ARPIs) had a higher OS compared to those receiving Lu‐177 PSMA‐617 RLT alone (18.2 vs 12.3 months, P =.265). The treatment was generally well‐tolerated, with manageable side effects such as anemia and thrombocytopenia. This study provides real‐world evidence supporting the effectiveness and safety of Lu‐177 PSMA‐617 RLT in mCRPC patients, particularly when used in combination with ARPIs. These findings contribute to the growing body of evidence on the potential benefits of PSMA‐targeted therapies in advanced prostate cancer. [ABSTRACT FROM AUTHOR]

Published
2024
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26. Prognostic significance of mucinous histology in left‑sided metastatic colorectal cancers with wild‑type RAS and evaluation of backbone chemotherapy regimens

Author

Arikan, Rukiye, primary, Atci, Muhammed, additional, Ay, Seval, additional, Ayhan, Murat, additional, Demircan, Nazim, additional, Telli, Tuğba, additional, Çelebi, Abdussamet, additional, Yaşar, Alper, additional, Işik, Selver, additional, Celikel, Cigdem, additional, Balvan, Ozlem, additional, Bayoglu, Ibrahim, additional, Kostek, Osman, additional, Dane, Faysal, additional, and Yumuk, Perran, additional

Published
2023
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27. Composite Kernels for Automatic Relevance Determination in Computerized Diagnosis of Alzheimer’s Disease

Author

Ayhan, Murat Seckin, Benton, Ryan G., Raghavan, Vijay V., Choubey, Suresh, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Imamura, Kazayuki, editor, Usui, Shiro, editor, Shirao, Tomoaki, editor, Kasamatsu, Takuji, editor, Schwabe, Lars, editor, and Zhong, Ning, editor

Published
2013
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32. The percentage of ALK-positive cells and the efficacy of first-line alectinib in advanced non-small cell lung cancer: is it a novel factor for stratification? (Turkish Oncology Group Study)

Author

Hizal, Mutlu, primary, Bilgin, Burak, additional, Paksoy, Nail, additional, Atcı, Muhammed Mustafa, additional, Kahraman, Seda, additional, Kılıçkap, Saadettin, additional, Güven, Deniz Can, additional, Keskinkılıç, Merve, additional, Ayhan, Murat, additional, Eren, Önder, additional, Mustafayev, Fatma Nihan Akkoç, additional, Yaman, Şebnem, additional, Bayram, Ertuğrul, additional, Ertürk, İsmail, additional, Özcan, Erkan, additional, Korkmaz, Mustafa, additional, Akagündüz, Baran, additional, Erdem, Dilek, additional, Telli, Tuğba Akın, additional, Aksoy, Asude, additional, Üskent, Necdet, additional, Baytemür, Naziyet Köse, additional, Gülmez, Ahmet, additional, Aydın, Dinçer, additional, Şakalar, Teoman, additional, Arak, Hacı, additional, Tatlı, Ali Murat, additional, Ergün, Yakup, additional, Ak, Naziye, additional, Ünal, Çağlar, additional, Özgün, Mehmet Alpaslan, additional, Yalçın, Bülent, additional, Öztop, İlhan, additional, Algın, Efnan, additional, Sakin, Abdullah, additional, Aydıner, Adnan, additional, Yumuk, Perran Fulden, additional, and Şendur, Mehmet Ali Nahit, additional

Published
2022
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34. Real-world data on efficacy and safety of first-line alectinib treatment in advanced-stage, ALK-positive non-small-cell lung cancer patients: a Turkish Oncology Group study

Author

Hizal, Mutlu, primary, Bilgin, Burak, additional, Paksoy, Nail, additional, Kılıçkap, Saadettin, additional, Atcı, Muhammed Mustafa, additional, Kahraman, Seda, additional, Keskinkılıç, Merve, additional, Bilgetekin, İrem, additional, Ayhan, Murat, additional, Tural, Deniz, additional, Eren, Önder, additional, Akkoç Mustafayev, Fatma Nihan, additional, Yaman, Şebnem, additional, Tatlı, Ali Murat, additional, Bayram, Ertuğrul, additional, Kutlu, Yasin, additional, Ertürk, İsmail, additional, Özcan, Erkan, additional, Gülmez, Ahmet, additional, Korkmaz, Mustafa, additional, Akagündüz, Baran, additional, Erdem, Dilek, additional, Telli, Tuğba Akın, additional, Aksoy, Asude, additional, Üskent, Necdet, additional, İriağaç, Yakup, additional, Baytemür, Naziyet Köse, additional, Aydın, Dinçer, additional, Şakalar, Teoman, additional, Arak, Hacı, additional, Selçukbiricik, Fatih, additional, Ergün, Yakup, additional, Korkmaz, Taner, additional, Ak, Naziye, additional, Ünal, Çağlar, additional, Akdeniz, Nadiye, additional, Özgün, Mehmet Alpaslan, additional, Öksüzoğlu, Berna, additional, Yalçın, Bülent, additional, Öztop, İlhan, additional, Algın, Efnan, additional, Sakin, Abdullah, additional, Aydıner, Adnan, additional, Yumuk, Perran Fulden, additional, and Nahit Şendur, Mehmet Ali, additional

Published
2022
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35. The effectiveness and safety of neoadjuvant pertuzumab and trastuzumab in women with locally advanced, inflammatory, or early-stage human epidermal growth factor receptor 2-positive breast cancer: Turkish Oncology Group study

Author

Özdemir, Özlem, primary, Zengel, Baha, additional, Yildiz, Yaşar, additional, Uluç, Basak Oyan, additional, Cabuk, Devrim, additional, Ozden, Ercan, additional, Salim, Derya Kivrak, additional, Paydas, Semra, additional, Demir, Atakan, additional, Diker, Omer, additional, Pilanci, Kezban Nur, additional, Sönmez, Özlem Uysal, additional, Vatansever, Sezai, additional, Dogan, Izzet, additional, Gulmez, Ahmet, additional, Cakar, Burcu, additional, Gursoy, Pinar, additional, Yildirim, Mahmut Emre, additional, Ayhan, Murat, additional, Karadurmus, Nuri, additional, Aykan, Musa Baris, additional, Cevik, Gökcen Tugba, additional, Sakalar, Teoman, additional, Hacibekiroglu, Ilhan, additional, Gülbagci, Burcu Belen, additional, Dincer, Murat, additional, Garbioglu, Duygu Bayir, additional, Kemal, Yasemin, additional, Nayir, Erdinc, additional, Taskaynatan, Halil, additional, Yilmaz, Mesut, additional, Avci, Okan, additional, Sari, Murat, additional, Coban, Ezgi, additional, Atci, Muhammed Mustafa, additional, Esen, Selin Aktürk, additional, Telli, Tugba Akin, additional, Karatas, Fatih, additional, Inal, Ali, additional, Demir, Hacer, additional, Kalkan, Nurhan Onal, additional, Yilmaz, Cengiz, additional, Tasli, Funda, additional, and Alacacioglu, Ahmet, additional

Published
2022
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37. Is the benefit of using adjuvant capecitabine in patients with residual triple-negative breast cancer related to pathological response to neoadjuvant chemotherapy?

Author

Dülgar, Özgecan, primary, Öven, Başak Bala, additional, Atcı, Muhammed Mustafa, additional, Arıkan, Rukiye, additional, Ay, Seval, additional, Ayhan, Murat, additional, Selvi, Oğuzhan, additional, Ozyukseler, Deniz Tataroglu, additional, Bayram, Ertuğrul, additional, Özcan, Erkan, additional, Yasin, Ayşe İrem, additional, and Gümüş, Mahmut, additional

Published
2022
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38. Real life experience of patients with locally advanced gastric and gastroesophageal junction adenocarcinoma treated with neoadjuvant chemotherapy: a Turkish oncology group study

Author

Başoğlu, Tuğba, primary, Sakin, Abdullah, additional, Erol, Cihan, additional, Özden, Ercan, additional, Çabuk, Devrim, additional, Çılbır, Ebru, additional, Tataroğlu Özyükseler, Deniz, additional, Ayhan, Murat, additional, Şendur, Mehmet Ali, additional, Dogan, Mutlu, additional, Öksüzoğlu, Berna, additional, Eryılmaz, Melek Karakurt, additional, Er, Özlem, additional, Taşçı, Elif Şenocak, additional, Özyurt, Neslihan, additional, Dülgar, Özgecan, additional, Özen, Miraç, additional, Hacıbekiroğlu, İlhan, additional, Öner, İrem, additional, Bekmez, Esma Türkmen, additional, Çağrı Yıldırım, Hasan, additional, Yalçın, Şuayib, additional, Paydaş, Semra, additional, Yekedüz, Emre, additional, Aksoy, Asude, additional, Özçelik, Melike, additional, Oyman, Abdilkerim, additional, Almuradova, Elvina, additional, Karabulut, Bülent, additional, Demir, Nazan, additional, Dinçer, Murat, additional, Özdemir, Nuriye, additional, Erdem, Dilek, additional, Ak, Naziye, additional, İnal, Ali, additional, Salim, Derya Kıvrak, additional, Deniz, Gülhan İpek, additional, Şakalar, Teoman, additional, Gülmez, Ahmet, additional, Kaçan, Turgut, additional, Özdemir, Özlem, additional, Alan, Özkan, additional, Ünal, Çağlar, additional, Karakaş, Yusuf, additional, Turhal, Serdar, additional, and Yumuk, Perran Fulden, additional

Published
2022
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39. The percentage of ALK-positive cells and the efficacy of first-line alectinib in advanced non-small cell lung cancer: is it a novel factor for stratification? (Turkish Oncology Group Study)

Author

Yumuk, Perran Fulden, Hızal, Mutlu; Bilgin, Burak; Paksoy, Nail; Atçı, Muhammed Mustafa; Kahraman, Seda; Kılıçkap, Saadettin; Güven, Deniz Can; Keskinkılıç, Merve; Ayhan, Murat; Eren, Önder; Mustafayev, Fatma Nihan Akkoç; Yaman, Şebnem; Bayram, Ertuğrul; Ertürk, İsmail; Özcan, Erkan; Korkmaz, Mustafa; Akagündüz, Baran; Erdem, Dilek; Telli, Tugba Akin; Aksoy, Asude; Uskent, Necdet; Baytemur, Naziyet Köse; Gülmez, Ahmet; Aydın, Dinçer; Sakalar, Teoman; Arak, Hacı; Tatlı, Ali Murat; Ergün, Yakup; Ak, Naziye; Ünal, Çağlar; Özgün, Mehmet Alpaslan; Yalçın, Bülent; Öztop, İlhan; Algın, Efnan; Sakin, Abdullah; Aydıner, Adnan; Sendur, Mehmet Ali Nahit, School of Medicine, Yumuk, Perran Fulden, Hızal, Mutlu; Bilgin, Burak; Paksoy, Nail; Atçı, Muhammed Mustafa; Kahraman, Seda; Kılıçkap, Saadettin; Güven, Deniz Can; Keskinkılıç, Merve; Ayhan, Murat; Eren, Önder; Mustafayev, Fatma Nihan Akkoç; Yaman, Şebnem; Bayram, Ertuğrul; Ertürk, İsmail; Özcan, Erkan; Korkmaz, Mustafa; Akagündüz, Baran; Erdem, Dilek; Telli, Tugba Akin; Aksoy, Asude; Uskent, Necdet; Baytemur, Naziyet Köse; Gülmez, Ahmet; Aydın, Dinçer; Sakalar, Teoman; Arak, Hacı; Tatlı, Ali Murat; Ergün, Yakup; Ak, Naziye; Ünal, Çağlar; Özgün, Mehmet Alpaslan; Yalçın, Bülent; Öztop, İlhan; Algın, Efnan; Sakin, Abdullah; Aydıner, Adnan; Sendur, Mehmet Ali Nahit, and School of Medicine

Abstract

Introduction Alectinib is an effective second-generation ALK tyrosine kinase inhibitor (TKI) used in the first-line treatment of patients with advanced ALK-positive NSCLC. Recent studies demonstrated that the percentage of ALK-positive tumor cells in patient groups receiving crizotinib might affect outcomes. This study aimed to investigate whether the percentage of ALK-positive cells had a predictive effect in patients with advanced NSCLC who received first-line Alectinib as ALK-TKI. Materials and methods This retrospective study included patients with advanced-stage NSCLC who received alectinib as a first-line ALK-TKI and whose percentage of ALK-positive cells was determined by FISH at 27 different centers. Patients who received any ALK-TKI before alectinib were not included in the study. Patients were separated into two groups according to the median (40%) value of the percentage of ALK-positive cells (high-positive group >= 40% and low-positive group < 40%). The primary endpoint was PFS, and the secondary endpoints were OS, ORR, and PFS of the subgroups based on different threshold values for the percentage of ALK-positive cells. Results 211 patients were enrolled (48.3% female, 51.7% male) to study. 37% (n = 78) of the patients had received chemotherapy previously. After a median of 19.4 months of follow-up, the median PFS was not reached in the high-positive group (n = 113), but it was 10.8 months in the low-positive group (n = 98) (HR 0.39; 95% CI 0.25-0.60, p < 0.001). The median OS in the high-positive group was not reached, whereas it was 22.8 months in the low-positive group (HR 0.37; 95% CI 0.22-0.63, p < 0.001). ORR was significantly higher in the high-positive group (87.2 vs. 68.5%; p = 0.002). According to the cut-off values of < 20%, 20-39%, 40-59%, and >= 60%, the median PFS was 4.5, 17.1, and 26 months, respectively, and could not be reached in the >= 60% group. Conclusion Our study demonstrated that the efficacy of alectinib varies significantly ac, NA

Published
2022

42. The impact of adjuvant oxaliplatin and tumor sidedness on the overall survival of stage IIB colon cancer patients: a multicentre study

Author

Atci, Muhammed Mustafa, primary, Akagunduz, Baran, additional, Demir, Metin, additional, Arikan, Rukiye, additional, Ay, Seval, additional, Ozer, Muhammet, additional, Ayhan, Murat, additional, Cil, Ibrahim, additional, Demir, Nazan, additional, Ozyurt, Neslihan, additional, Karakaya, Gökhan, additional, Cevik, Gokcen Tugba, additional, Onder, Arif Hakan, additional, Selvi, Oguzhan, additional, and Sakin, Abdullah, additional

Published
2022
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43. Politik davranış algısı ile tükenmişlik ve işyeri nezaketsizliği arasındaki ilişki üzerine bir araştırma

Author

Ayhan, Murat, Gök, Sibel, Marmara Üniversitesi, Sosyal Bilimler Enstitüsü, Çalışma Ekonomisi ve Endüstri İlişkileri Anabilim Dalı, and Yönetim ve Çalışma Psikolojisi Bilim Dalı

Subjects
İşyeri Nezaketsizliği Perception of Political Behavior, Politik Davranış Algısı, Burnout, Tükenmişlik, Workplace Invivility
Abstract

Bu tez çalışmasının amacı; çalışanların algıladıkları politik davranışların tükenmişlik düzeylerini ve işyeri nezaketsizliği sergilemelerini ne ölçüde etkilediğinin araştırılmasıdır. Araştırma dört bölümden oluşmaktadır. Birinci bölümde politik davranış algısı, ikinci bölümde tükenmişlik, üçüncü bölümde işyeri nezaketsizliği, dördüncü bölümde ise idari ve yargısal alanda faaliyet gösteren bir kamu kurumunun İstanbul’daki kurumunda çalışan 122 kişi üzerinden anket tekniği ile elde edilen verilerin analizine ve bulgularına yer verilmiştir. Tezin anket uygulamasında veri toplama aracı olarak Politik Davranış Ölçeği, Tükenmişlik Ölçeği, İşyeri Nezaketsizliği Ölçeği ve Kişisel Bilgi Formu kullanılarak elde edilen veriler IBM SPSS Statistics 25.0 ve IBM SPSS Amos paket programları aracılığıyla analiz edilmiştir. Araştırmada; politik davranış algısı ile tükenmişlik ve alt boyutlarından duygusal tükenme ve duyarsızlaşma arasında orta düzeyli, pozitif ve anlamlı bir ilişki tespit edilirken politik davranış algısı ile kişisel başarıda düşme hissi alt boyutunda anlamlı bir ilişki olmadığı sonucuna ulaşılmıştır. Ayrıca politik davranış algısı ile işyeri nezaketsizliği sergileme sıklığı arasında da orta düzeyli, pozitif ve anlamlı bir ilişki tespit edilmiştir. The aim of this thesis study is to research the extent to find out to what extent employees' perceived political behaviors affect burnout levels and workplace incivility. The research consists of four parts. Part 1 includes the perception of political behavior, in the second part introduces Burnout. Part 3 includes workplace incivility, in the fourth part introduces the analysis and findings of the data gathered by the survey technique from 122 employees working at Office of public institution operating in the administrative and judicial field in İstanbul In the field study of the thesis, the Political Behavior Scale, Burnout Scale, Workplace Incivility Scale and Personal Information Form were used as data tool collection. The data obtained from the surveys were analyzed with the IBM SPSS Statistics 25.0 and IBM SPSS Amos package programs. In the research; while it was determined that there is a moderate, positive and significant relationship between the perception of political behavior and burnout and its sub-dimensions of emotional exhaustion and depersonalization, there was no significant relationship between the perception of political behavior and the feeling of falling in personal achievement. In addition, it was found that there was a a moderate, positive and significant relationship between the perception of political behavior and the frequency of exhibiting of workplace incivility.

Published
2022

44. Classifying Compensations in Construction Disputes Using Machine Learning Techniques

Author

Ayhan, Murat, Dikmen Toker, İrem, and Birgönül, Mustafa Talat

Subjects
General Engineering
Abstract

It is highly probable to encounter disputes in construction projects and construction disputes are detrimental as they may lead to cost overruns and delays. Knowing the compensation with some certainty can avoid parties from extending inconclusive claims. Decision support systems can be helpful to understand the aspect of the compensation, if any compensation can be acquired. Within this context, the primary objective of this research is to predict the associated compensations in construction disputes by using machine learning (ML) techniques on past project data so that in new projects, decision support can be provided with some certainty via forecasts on the aspect of the compensation. To do this, a conceptual model identifying the attributes affecting compensations was established based on an extensive literature review. Using these attributes, data from real-world dispute cases were collected. Insignificant attributes were eliminated via Chi-square tests to establish a simpler classification model, which was experimented via alternative single and ensemble ML techniques. The Naïve Bayes (NB) classifier generated the highest average classification accuracy as 80.61% when One-vs-All (OvA) decomposition technique was utilized. The conceptual model can guide construction professionals during dispute management decision-making and the promising results indicate that the classification model has the potential to identify compensations. This study can be used to mitigate disputes by preventing parties from resorting to unpleasant and inconclusive resolution processes.

Published
2021

45. Real life experience of patients with locally advanced gastric and gastroesophageal junction adenocarcinoma treated with neoadjuvant chemotherapy: a Turkish oncology group study.

Author

Başoğlu, Tuğba, Sakin, Abdullah, Erol, Cihan, Özden, Ercan, Çabuk, Devrim, Çılbır, Ebru, Tataroğlu Özyükseler, Deniz, Ayhan, Murat, Şendur, Mehmet Ali, Dogan, Mutlu, Öksüzoğlu, Berna, Eryılmaz, Melek Karakurt, Er, Özlem, Taşçı, Elif Şenocak, Özyurt, Neslihan, Dülgar, Özgecan, Özen, Miraç, Hacıbekiroğlu, İlhan, Öner, İrem, and Bekmez, Esma Türkmen

Published
2023
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46. Second-line Therapy after Trastuzumab Failure in HER2-Positive Metastatic Gastric Cancer: A Real-life Data.

Author

Topcu, Atakan, Besiroglu, Mehmet, Atci, Muhammed Mustafa, Secmeler, Saban, Ayhan, Murat, Ozkan, Metin, Bozkurt, Oktay, Urakci, Zuhat, Ay, Seval, Geredeli, Caglayan, Yasin, Ayse Irem, Pasin, Ozge, and Turk, Haci Mehmet

Subjects
THERAPEUTIC use of antineoplastic agents, STOMACH tumors, STATISTICS, FOLINIC acid, CONFIDENCE intervals, ONCOGENES, TRASTUZUMAB, LOG-rank test, METASTASIS, RETROSPECTIVE studies, IRINOTECAN, TREATMENT failure, TREATMENT effectiveness, PEARSON correlation (Statistics), FLUOROURACIL, QUALITATIVE research, SURVIVAL analysis (Biometry), DESCRIPTIVE statistics, KAPLAN-Meier estimator, CHI-squared test, DATA analysis software, PACLITAXEL, PROPORTIONAL hazards models
Abstract

Objectives: To compare the second-line treatments on survival after trastuzumab failure in HER2-positive metastatic gastric cancer. Methods: We retrospectively included 57 patients. Of whom, 32 (56%) received paclitaxel, whereas 25 (44%) received 5-fluorouracil, leucovorin, and irinotecan (FOLFIRI). We analyzed the patient characteristics, and survival outcomes of the second-line treatment. Results: The median PFS was 3.5 months in the paclitaxel-group and 4.8 months in the FOLFIRI-group (p=0.569). The median overall survival (OS) was 6.0 months in paclitaxel-group and 11.0 months in FOLFIRI-group (p=0.410). FOLFIRI provided a significant OS advantage over paclitaxel in patients with grade 3 tumors or who did not have an objective first-line treatment response. Conclusion: FOLFIRI may be recommended as a preferred option over paclitaxel in patients with these identified risk factors. [ABSTRACT FROM AUTHOR]

Published
2023
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47. Disputes Using Machine Learning Techniques Classifying Compensations in Construction.

Author

Ayhan, Murat, Dikmen, Irem, and Birgonul, M. Talat

Subjects
*DECISION support systems, *LITERATURE reviews, *COST overruns, *CONSTRUCTION projects, *MACHINE learning, *CONCEPTUAL models
Abstract

It is highly probable to encounter disputes in construction projects and construction disputes are detrimental as they may lead to cost overruns and delays. Knowing the compensation with some certainty can avoid parties from extending inconclusive claims. Decision support systems can be helpful to understand the aspect of the compensation, if any compensation can be acquired. Within this context, the primary objective of this research is to predict the associated compensations in construction disputes by using machine learning (ML) techniques on past project data so that in new projects, decision support can be provided with some certainty via forecasts on the aspect of the compensation. To do this, a conceptual model identifying the attributes affecting compensations was established based on an extensive literature review. Using these attributes, data from real-world dispute cases were collected. Insignificant attributes were eliminated via Chi-square tests to establish a simpler classification model, which was experimented via alternative single and ensemble ML techniques. The Naïve Bayes (NB) classifier generated the highest average classification accuracy as 80.61% when One-vs-All (OvA) decomposition technique was utilized. The conceptual model can guide construction professionals during dispute management decisionmaking and the promising results indicate that the classification model has the potential to identify compensations. This study can be used to mitigate disputes by preventing parties from resorting to unpleasant and inconclusive resolution processes. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
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