Doç. Dr. ÖZER ÇELİK | AVESİS

Akademik Veri Yönetim Sistemi

Yayınlar & Eserler

Makaleler 77

1. Development of a Preliminary Diagnostic Tool for the Segmentation of Benign Jaw Lesions in CBCT Images Using nnU-Net v2: An Artificial Intelligence–Based Approach

Başar K. D., Gülşen İ. T., KURAN A., EVLİ C., BAYDAR O., BİLGİR E., et al.

Journal of Imaging Informatics in Medicine , 2026 (SCI-Expanded, Scopus)

2. Segmentation-Based Multi-Class Detection and Radiographic Charting of Periodontal and Restorative Conditions on Bitewing Radiographs Using Deep Learning

Bayırlı A. B., Kesgin B., Uytun M., KURAN A., Çitir M., YAVUZ M. B., et al.

Diagnostics , cilt.16, sa.2, 2026 (SCI-Expanded, Scopus)

3. Deep learning-based 3D automatic segmentation of impacted canines in CBCT scans

Unal T., KURAN A., Gulsen I. T., KIZILAY F. N., Gulsen E., Ozudogru S., et al.

BMC ORAL HEALTH , cilt.25, sa.1, 2025 (SCI-Expanded, Scopus)

4. AI in Temporomandibular Joint Imaging

Bayrakdar İ. Ş., Kuran A., Çelik Ö., Orhan K.

NEUROIMAGING CLINICS OF NORTH AMERICA , cilt.35, sa.4, ss.527-537, 2025 (SCI-Expanded, Scopus)

5. Deploying a novel deep learning framework for segmentation of specific anatomical structures on cone-beam CT

Yuce F., Buyuk C., Bilgir E., Çelik Ö., Bayrakdar İ. Ş.

ORAL RADIOLOGY , cilt.41, sa.4, ss.562-570, 2025 (SCI-Expanded, Scopus)

6. Artificial Intelligence for Root Canal Orifice Identification Using Dental Operating Microscope Images: A Preliminary Evaluation

KARATAŞ E., Ünal O., ÇELİK Ö., BAYRAKDAR İ. Ş.

Australian Endodontic Journal , cilt.51, sa.2, ss.407-414, 2025 (SCI-Expanded, Scopus)

7. A Novel Machine Learning Model for Predicting Natural Conception Using Non-Laboratory-Based Data

KAYA Y., Aydın Y., Kaya C., Tahta T., ÇELİK Ö.

Reproductive Sciences , cilt.32, sa.8, ss.2644-2653, 2025 (SCI-Expanded, Scopus)

8. Automatic Segmentation of the Infraorbital Canal in CBCT Images: Anatomical Structure Recognition Using Artificial Intelligence

Gumussoy I., Haylaz E., DUMAN Ş. B., Kalabalık F., Eren M. C., Say S., et al.

DIAGNOSTICS , cilt.15, sa.13, 2025 (SCI-Expanded, Scopus)

9. Evaluation of Cone-Beam Computed Tomography Images with Artificial Intelligence

Arı T., BAYRAKDAR İ. Ş., ÇELİK Ö., BİLGİR E., KURAN A., ORHAN K.

JOURNAL OF IMAGING INFORMATICS IN MEDICINE , 2025 (SCI-Expanded, Scopus)

10. Postkontrast T1 Agırlıklı Görüntülerde Meningeal Kontrastlanmanın Derin Öğrenme Yöntemi İle Segment

Aydın N., Saylisoy S., toprak u., MERT B., Çelik Ö.

Osmangazi Tıp Dergisi , cilt.47, sa.4, ss.600-605, 2025 (TRDizin)

11. AI-powered segmentation of bifid mandibular canals using CBCT

Gumussoy I., Demirezer K., Duman Ş. B., Haylaz E., Bayrakdar İ. Ş., Çelik Ö., et al.

BMC ORAL HEALTH , cilt.25, sa.1, 2025 (SCI-Expanded, Scopus)

12. Automatic Segmentation of the Nasolacrimal Canal: Application of the nnU-Net v2 Model in CBCT Imaging

Haylaz E., Gumussoy I., DUMAN Ş. B., Kalabalik F., Eren M. C., Demirsoy M. S., et al.

JOURNAL OF CLINICAL MEDICINE , cilt.14, sa.3, 2025 (SCI-Expanded, Scopus)

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13. SunCloud: A mobile application for children with urinary incontinence

AÇIKGÖZ A., ÇAKIRLI M., TOKAR B., ÇELİK Ö.

Journal of Evaluation in Clinical Practice , cilt.31, sa.1, 2025 (SCI-Expanded, Scopus)

14. Evaluation of the Detectability of Oral Potentially Malignant Diseases with a Deep Learning Approach: A Retrospective Pilot Study

KESER G., Yülek H., BAYRAKDAR İ. Ş., NAMDAR PEKİNER F. M., ÇELİK Ö.

Journal of Imaging Informatics in Medicine , 2025 (SCI-Expanded, Scopus)

15. Machine Learning-Based Prediction of Prostate Biopsy Necessity Using PSA, MRI, and Hematologic Parameters

Sungur M., Aykac A., Aydin M. E., ÇELİK Ö., Kaya C.

JOURNAL OF CLINICAL MEDICINE , sa.1, 2025 (SCI-Expanded, Scopus)

16. DEEP LEARNING MODEL USING YOLO-V5 FOR DETECTING AND NUMBERING OF TEETH IN DENTAL BITEWING IMAGES

Görürgöz C., Chaurasia A., Karobari M. I., BAYRAKDAR İ. Ş., ÇELİK Ö., ORHAN K.

Journal of Stomatology , cilt.78, sa.1, ss.42-51, 2025 (Scopus)

17. Risk Assessment for Preeclampsia in the Preconception Period Based on Maternal Clinical History via Machine Learning Methods

KAYA Y., Butun Z., ÇELİK Ö., Salik E. A., Tahta T.

JOURNAL OF CLINICAL MEDICINE , cilt.14, sa.1, 2025 (SCI-Expanded, Scopus)

18. The prediction of semen quality based on lifestyle behaviours by the machine learning based models

Aykac A., Kaya C., ÇELİK Ö., Aydin M. E., Sungur M.

REPRODUCTIVE BIOLOGY AND ENDOCRINOLOGY , cilt.22, sa.1, 2024 (SCI-Expanded, Scopus)

19. Developing a machine learning model for predicting varicocelectomy outcomes: a pilot study

Kaya C., Aydin M. E., ÇELİK Ö., Aykac A., Sungur M.

JOURNAL OF MENS HEALTH , sa.12, ss.65-74, 2024 (SCI-Expanded, SSCI, Scopus)

20. Evaluation of tooth development stages with deep learning-based artificial intelligence algorithm

KURT A., GÜNAÇAR D. N., Şılbır F. Y., Yeşil Z., BAYRAKDAR İ. Ş., ÇELİK Ö., et al.

BMC Oral Health , cilt.24, sa.1, 2024 (SCI-Expanded, Scopus)

21. YOLO-V5 based deep learning approach for tooth detection and segmentation on pediatric panoramic radiographs in mixed dentition

Beser B., Reis T., Berber M. N., Topaloglu E., Gungor E., Kılıc M. C., et al.

BMC Medical Imaging , cilt.24, sa.1, 2024 (SCI-Expanded, Scopus)

22. The early prediction of gestational diabetes mellitus by machine learning models

KAYA Y., Butun Z., ÇELİK Ö., Salik E. A., Tahta T., ALTIN YAVUZ A.

BMC PREGNANCY AND CHILDBIRTH , cilt.24, sa.1, 2024 (SCI-Expanded, Scopus)

23. Automatic maxillary sinus segmentation and pathology classification on cone-beam computed tomographic images using deep learning

ALTUN O., Özen D. Ç., DUMAN Ş. B., DEDEOĞLU N., BAYRAKDAR İ. Ş., Eşer G., et al.

BMC Oral Health , cilt.24, sa.1, 2024 (SCI-Expanded, Scopus)

24. A deep learning approach to detection of oral cancer lesions from intra oral patient images: A preliminary retrospective study

KESER G., NAMDAR PEKİNER F. M., BAYRAKDAR İ. Ş., ÇELİK Ö., ORHAN K.

Journal of Stomatology, Oral and Maxillofacial Surgery , cilt.125, sa.5, 2024 (SCI-Expanded, Scopus)

25. Prediction of extraction difficulty for impacted maxillary third molars with deep learning approach

Torul D., Akpinar H., BAYRAKDAR İ. Ş., ÇELİK Ö., ORHAN K.

Journal of Stomatology, Oral and Maxillofacial Surgery , cilt.125, sa.4, 2024 (SCI-Expanded, Scopus)

26. Predicting mothers' exclusive breastfeeding for the first 6 months: Interface creation study using machine learning technique

AÇIKGÖZ A., ÇAKIRLI M., Şahin B. M., ÇELİK Ö.

Journal of Evaluation in Clinical Practice , cilt.30, sa.6, ss.1000-1007, 2024 (SCI-Expanded, Scopus)

27. A Deep Learning Approach to Automatic Tooth Caries Segmentation in Panoramic Radiographs of Children in Primary Dentition, Mixed Dentition, and Permanent Dentition

Asci E., Kilic M., ÇELİK Ö., Cantekin K., Bircan H. B., BAYRAKDAR İ. Ş., et al.

Children , cilt.11, sa.6, 2024 (SCI-Expanded, Scopus)

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28. Tooth numbering and classification on bitewing radiographs: an artificial intelligence pilot study

Altındağ A., Bahrilli S., ÇELİK Ö., BAYRAKDAR İ. Ş., ORHAN K.

Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology , cilt.137, sa.6, ss.679-689, 2024 (SCI-Expanded, Scopus)

29. Artificial intelligence system for automatic maxillary sinus segmentation on cone beam computed tomography images

BAYRAKDAR İ. Ş., Elfayome N. S., Hussien R. A., Gulsen I. T., KURAN A., Gunes I., et al.

DENTOMAXILLOFACIAL RADIOLOGY , cilt.53, ss.256-266, 2024 (SCI-Expanded, Scopus)

30. Second mesiobuccal canal segmentation with YOLOv5 architecture using cone beam computed tomography images

Duman Ş. B., Çelik Özen D., Bayrakdar İ. Ş., Baydar O., Alhaija E. S. A., Helvacioğlu Yiğit D., et al.

Odontology , cilt.112, sa.2, ss.552-561, 2024 (SCI-Expanded, Scopus)

31. DEVELOPMENT OF MOBILE EDUCATIONAL MATERIAL FOR NURSES: A PROCESS IMPROVEMENT STUDY

ÖZKARAMAN A., KERSU Ö., UZGÖR F., ÇAKIRLI M., ÇELİK Ö., DANACI B., et al.

TURKISH ONLINE JOURNAL OF DISTANCE EDUCATION , cilt.25, 2024 (ESCI, Scopus)

32. An artificial intelligence study: automatic description of anatomic landmarks on panoramic radiographs in the pediatric population

Bağ İ., Bilgir E., Bayrakdar İ. Ş., Baydar O., Atak F. M., Çelik Ö., et al.

BMC Oral Health , cilt.23, sa.1, 2023 (SCI-Expanded, Scopus)

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33. A Deep Learning Approach to Automatic Tooth Detection and Numbering in Panoramic Radiographs: An Artificial Intelligence Study

MERTOĞLU D., KESER G., NAMDAR PEKİNER F. M., BAYRAKDAR İ. Ş., ÇELİK Ö., ORHAN K.

CLINICAL AND EXPERIMENTAL HEALTH SCIENCES , cilt.13, sa.4, ss.883-888, 2023 (ESCI, TRDizin)

34. Detecting Pulp Stones with Automatic Deep Learning in Bitewing Radiographs: A Pilot Study of Artiőcial Intelligence

ALTINDAĞ A., Uzun S., BAYRAKDAR İ. Ş., ÇELİK Ö.

European annals of dental sciences (Online) , cilt.50, sa.1, ss.12-16, 2023 (TRDizin)

35. A deep learning algorithm for classification of oral lichen planus lesions from photographic images: A retrospective study

KESER G., BAYRAKDAR İ. Ş., Pekiner F. N., ÇELİK Ö., ORHAN K.

Journal of Stomatology, Oral and Maxillofacial Surgery , cilt.124, sa.1, 2023 (SCI-Expanded, Scopus) Sürdürülebilir Kalkınma

Sürdürülebilir Kalkınma

36. Deep-Learning-Based Automatic Segmentation of Parotid Gland on Computed Tomography Images

ÖNDER M., EVLİ C., Türk E., KAZAN O., BAYRAKDAR İ. Ş., ÇELİK Ö., et al.

Diagnostics , cilt.13, sa.4, 2023 (SCI-Expanded, Scopus)

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37. Response Prediction in Lung SBRT with Artificial Intelligence

ETİZ D., Yakar M., AK G., KÜTRİ D., ÇELİK Ö., METİNTAŞ M.

Turk Onkoloji Dergisi , cilt.38, sa.3, ss.288-294, 2023 (ESCI, Scopus, TRDizin)

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38. Automated Mesiodens Detection with Deep-Learning-Based System Using Cone-Beam Computed Tomography Images

Syed A. Z., ÇELİK ÖZEN D., Abdelkarim A. Z., DUMAN Ş. B., BAYRAKDAR İ. Ş., DUMAN S., et al.

International Journal of Intelligent Systems , cilt.2023, 2023 (SCI-Expanded, Scopus)

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39. Detecting the presence of taurodont teeth on panoramic radiographs using a deep learning-based convolutional neural network algorithm

DUMAN S., Yılmaz E. F., EŞER G., ÇELİK Ö., BAYRAKDAR İ. Ş., BİLGİR E., et al.

ORAL RADIOLOGY , cilt.39, sa.1, ss.207-214, 2023 (SCI-Expanded, Scopus)

40. Segmentation of acute pulmonary embolism in computed tomography pulmonary angiography using the deep learning method Derin öğrenme yöntemiyle akut pulmoner embolinin bilgisayarlı tomografik pulmoner anjiografide segmentasyonu

AYDIN N., CİHAN Ç., ÇELİK Ö., ASLAN A. F., ODABAŞ A., ALATAŞ F., et al.

Tuberkuloz ve Toraks , cilt.71, sa.2, ss.131-137, 2023 (ESCI, Scopus, TRDizin)

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41. Automatic Feature Segmentation in Dental Periapical Radiographs

ARI T., SAĞLAM H., ÖKSÜZOĞLU H., KAZAN O., BAYRAKDAR İ. Ş., DUMAN Ş. B., et al.

Diagnostics , cilt.12, sa.12, 2022 (SCI-Expanded, Scopus)

42. A deep learning approach for masseter muscle segmentation on ultrasonography

KESER G., BAYRAKDAR İ. Ş., NAMDAR PEKİNER F. M., ÇELİK Ö., ORHAN K.

JOURNAL OF ULTRASONOGRAPHY , cilt.22, sa.91, 2022 (ESCI, Scopus)

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43. Deep-learning approach for caries detection and segmentation on dental bitewing radiographs

Bayrakdar İ. Ş., Orhan K., Akarsu S., Çelik Ö., Atasoy S., Pekince A., et al.

ORAL RADIOLOGY , cilt.38, sa.4, ss.468-479, 2022 (SCI-Expanded, Scopus)

44. Convolutional Neural Network Performance for Sella Turcica Segmentation and Classification Using CBCT Images

DUMAN Ş. B., Syed A. Z., ÇELİK ÖZEN D., BAYRAKDAR İ. Ş., Salehi H. S., Abdelkarim A., et al.

DIAGNOSTICS , cilt.12, sa.9, 2022 (SCI-Expanded, Scopus)

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45. Diagnostic charting of panoramic radiography using deep-learning artificial intelligence system

Başaran M., Çelik Ö., Bayrakdar İ. Ş., Bilgir E., Orhan K., Odabaş A., et al.

ORAL RADIOLOGY , cilt.38, sa.3, ss.363-369, 2022 (SCI-Expanded, Scopus)

46. Combined clinical and specific positron emission tomography/computed tomography-based radiomic features and machine-learning model in prediction of thymoma risk groups

ÖZKAN E., ORHAN K., SOYDAL Ç., KAHYA Y., Seckin Tunc S., Celik O., et al.

Nuclear medicine communications , cilt.43, sa.5, ss.529-539, 2022 (SCI-Expanded, Scopus)

47. Optical properties of Nb2O5 doped ZnO nanocomposite thin film deposited by thermionic vacuum arc

PAT S., ÇELİK Ö., ODABAŞ A., KORKMAZ Ş.

Optik , cilt.258, 2022 (SCI-Expanded, Scopus)

48. Evaluation of acute hematological toxicity by machine learning in gynecologic cancers using postoperative radiotherapy.

Yakar M. Ç., Etiz D., Celik Ö., Ozen A.

Indian journal of cancer , cilt.59, sa.2, ss.178-186, 2022 (SCI-Expanded, Scopus) Sürdürülebilir Kalkınma

Sürdürülebilir Kalkınma

49. Performance of a convolutional neural network algorithm for tooth detection and numbering on periapical radiographs

Görürgöz C., Orhan K., Bayrakdar İ. Ş., Çelik Ö., Bilgir E., Odabaş A., et al.

DENTOMAXILLOFACIAL RADIOLOGY , cilt.51, sa.3, 2022 (SCI-Expanded, Scopus)

50. A DEEP-LEARNING MODEL FOR IDIOPATHIC OSTEOSCLEROSIS DETECTION ON PANORAMIC RADIOGRAPHS

Yesiltepe S., Bayrakdar İ. Ş., Orhan K., Çelik Ö., Bilgir E., Aslan A. F., et al.

MEDICAL PRINCIPLES AND PRACTICE , cilt.31, ss.555-561, 2022 (SCI-Expanded, Scopus)

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51. Derin Öğrenme Yöntemi Kullanılarak Geliştirilen Yapay Zekâ Yöntemi ile Panoramik Radyografilerde Dental Restorasyonların Otomatik Tespiti ve Sınıflandırılması: Metodolojik Çalışmalar

AŞÇI E., KILIÇ M., ÇELİK Ö., BAYRAKDAR İ. Ş., BİLGİR E., ASLAN A. F., et al.

Türkiye Klinikleri Diş Hekimliği Bilimleri Dergisi , cilt.28, 2022 (TRDizin)

52. A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs

Bayrakdar İ. Ş., Orhan K., Çelik Ö., Bilgir E., Sağlam H., Kaplan F. A., et al.

BIOMED RESEARCH INTERNATIONAL , cilt.2022, 2022 (SCI-Expanded, Scopus)

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53. Segmentation of orbital and periorbital lesions detected in orbital magnetic resonance imaging by deep learning method

AYDIN N., ŞAYLISOY S., Celik O., ASLAN A. F., ODABAŞ A.

Polish Journal of Radiology , cilt.87, sa.1, 2022 (ESCI, Scopus)

54. Application of Machine Learning Techniques for Enuresis Prediction in Children

Tokar B., Baskaya M., Celik Ö., Çemrek F., Acikgoz A.

EUROPEAN JOURNAL OF PEDIATRIC SURGERY , cilt.31, sa.05, ss.414-419, 2021 (SCI-Expanded, Scopus)

55. Artificial intelligence system for automatic deciduous tooth detection and numbering in panoramic radiographs.

Kılıc M. C., Bayrakdar İ. Ş., Çelik Ö., Bilgir E., Orhan K., Aydın O. B., et al.

Dento maxillo facial radiology , cilt.50, sa.6, ss.20200172, 2021 (SCI-Expanded, Scopus)

56. Can the blockchain-enabled interplanetary file system (Block-IPFS) be a solution for securely transferring imaging data for artificial intelligence research in oral and maxillofacial radiology?

Orhan K., Bayrakdar İ. Ş., Celik Ö., Ayan B., Polat E.

IMAGING SCIENCE IN DENTISTRY , cilt.51, sa.3, ss.337-339, 2021 (ESCI, Scopus)

57. Diş Hekimliğinde Yapay Zeka

SAĞLAM H., ARI T., BAYRAKDAR İ. Ş., BİLGİR E., UĞURLU M., ÇELİK Ö., et al.

Artificial Intelligence In Dentistry , 2021 (Hakemli Dergi)

58. An artificial intelligence approach to automatic tooth detection and numbering in panoramic radiographs

Bilgir E., Bayrakdar İ. Ş., Çelik Ö., Orhan K., Akkoca F., Sağlam H., et al.

BMC MEDICAL IMAGING , cilt.21, sa.1, 2021 (SCI-Expanded, Scopus)

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59. An artificial intelligence proposal to automatic teeth detection and numbering in dental bite-wing radiographs

Yasa Y., Celik Ö., BAYRAKDAR İ. Ş., PEKİNCE A., ORHAN K., Akarsu S., et al.

ACTA ODONTOLOGICA SCANDINAVICA , cilt.79, sa.4, ss.275-281, 2021 (SCI-Expanded, Scopus)

60. A pilot study of a deep learning approach to submerged primary tooth classification and detection.

Caliskan S., Tuloglu N., Celik Ö., Ozdemir C., Kizilaslan S., Bayrak Ş.

International journal of computerized dentistry , cilt.24, sa.1, ss.1-9, 2021 (SCI-Expanded, Scopus)

61. Detection of impacted teeth using deep learning technique

Comptes Rendus de L'Academie Bulgare des Sciences , cilt.74, sa.2, ss.269-277, 2021 (SCI-Expanded, Scopus)

62. Prediction of Radiation Pneumonitis With Machine Learning in Stage III Lung Cancer: A Pilot Study.

Yakar M. Ç., ETİZ D., METİNTAŞ M., AK G., Celik Ö.

Technology in cancer research & treatment , cilt.20, 2021 (SCI-Expanded, Scopus) Sürdürülebilir Kalkınma

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63. TF-IDF, Word2vec ve Fasttext Vektör Model Yöntemleri ile Türkçe Haber Metinlerinin Sınıflandırılması

ÇELİK Ö., Koç B. C.

Dokuz Eylül Üniversitesi Mühendislik Fakültesi Fen ve Mühendislik Dergisi , cilt.23, sa.67, ss.121-127, 2021 (TRDizin)

64. Contribution of artificial intelligence applications developed with the deep learning method to the diagnosis of COVID-19 pneumonia on computed tomography

AYDIN N., Celik O.

TUBERKULOZ VE TORAKS-TUBERCULOSIS AND THORAX , cilt.69, sa.4, ss.486-491, 2021 (ESCI, Scopus, TRDizin)

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65. Prediction of Response to Neoadjuvant Chemoradiotherapy with Machine Learning in Rectal Cancer: A Pilot Study

YAKAR M. Ç., ETİZ D., BADAK B., ÇELİK Ö., KÜTRİ D., ÖZEN A., et al.

TURK ONKOLOJI DERGISI , cilt.36, sa.4, ss.459-467, 2021 (ESCI, Scopus, TRDizin)

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66. Yeniden Örnekleme Teknikleri Kullanarak SMS Verisi Üzerinde Metin Sınıflandırma Çalışması

ÇELİK Ö., KAPLAN G.

Erciyes Üniversitesi Fen Bilimleri Enstitüsü Dergisi , cilt.36, sa.3, ss.433-442, 2020 (TRDizin)

67. Prediction of Survival and Recurrence Patterns by Machine Learning in Gastric Cancer Cases Undergoing Radiation Therapy and Chemotherapy

AKÇAY M. Ç., ETİZ D., çelik Ö.

ADVANCES IN RADIATION ONCOLOGY , cilt.5, sa.6, ss.1179-1187, 2020 (ESCI, Scopus)

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68. Success of artificial intelligence system in determining alveolar bone loss from dental panoramic radiography images

KURT BAYRAKDAR S., ÇELİK Ö., BAYRAKDAR İ. Ş., ORHAN K., BİLGİR E., ODABAŞ A., et al.

Cumhuriyet Dental Journal , cilt.23, sa.4, ss.318-324, 2020 (Hakemli Dergi)

69. Sign2Text: Konvolüsyonel Sinir Ağları Kullanarak Türk İşaret Dili Tanıma

ÇELİK Ö., ODABAŞ A.

Avrupa Bilim ve Teknoloji Dergisi , sa.19, ss.923-934, 2020 (TRDizin) Sürdürülebilir Kalkınma

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70. Estimation of renal scarring in children with lower urinary tract dysfunction by utilizing resampling technique and machine learning algorithms

Çelik Ö., Aslan A. F., Osmanoğlu U. Ö., Çetin N., Tokar B.

Journal of Surgery and Medicine , cilt.4, ss.573-577, 2020 (Hakemli Dergi)

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71. SENTIMENT ANALYSIS FROM SOCIAL MEDIA COMMENTS

ÇELİK Ö., Osmanoğlu U. Ö., Çanakçı B.

Mühendislik Bilimleri ve Tasarım Dergisi , cilt.8, sa.2, ss.366-374, 2020 (TRDizin)

72. Evaluation of Prognosis in Nasopharyngeal Cancer Using Machine Learning

Akcay M. Ç., ETİZ D., Celik Ö., ÖZEN A.

TECHNOLOGY IN CANCER RESEARCH & TREATMENT , cilt.19, 2020 (SCI-Expanded, Scopus)

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73. Gender Prediction from Social Media Comments with Artificial Intelligence

ÇELİK Ö., ASLAN A. F.

SAKARYA UNIVERSITY JOURNAL OF SCIENCE , cilt.23, sa.6, ss.1256-1264, 2019 (TRDizin)

74. Prediction of The Prices of Second-Hand Cars

ÇELİK Ö., Osmanoğlu U. Ö.

Avrupa Bilim ve Teknoloji Dergisi , sa.16, ss.77-83, 2019 (TRDizin)

75. Comparing to Techniques Used in Customer Churn Analysis

ÇELİK Ö., Osmanoğlu U. Ö.

Journal of Multidisciplinary Developments , cilt.4, sa.1, ss.30-38, 2019 (Hakemli Dergi)

76. A Research on Machine Learning Methods and Its Applications

ÇELİK Ö., ALTUNAYDIN S. S.

Journal of Educational Technology&Online Learning , cilt.1, sa.3, ss.25-40, 2018 (Hakemli Dergi)

77. Wear behavior of SiC-reinforced surface composite Al7075-T651 aluminum alloy produced using friction stir processing

SERT A., ÇELİK Ö.

Indian Journal of Engineering and Materials Sciences , cilt.21, sa.1, ss.35-43, 2014 (SCI-Expanded, Scopus)

Hakemli Bilimsel Toplantılarda Yayımlanmış Bildiriler 14

1. Detection of Mucous Retention Cysts of Maxillary Sinus (MRCMS) on Panoramic Radiographs with the YOLOv8 Model: A Pilot Study

ALTUNTAŞ K., KILIÇ E., BAYDAR O., YEŞİLOVA E., BİLGİR E., ÇELİK Ö., et al.

EADMFR 2025 Junior Meeting, Porto, Portekiz, 2 - 05 Şubat 2025, (Özet Bildiri)

2. AI-Based Segmentation of Bifid Mandibular Condyle in Panoramic Radiographs: A YOLOv8 vs YOLOv9 Comparison

KILIÇ E., BAYDAR O., YEŞİLOVA E., BİLGİR E., ÇELİK Ö., BAYRAKDAR İ. Ş., et al.

EADMFR 2025 Junior Meeting, Porto, Portekiz, 2 - 05 Şubat 2025, (Özet Bildiri)

3. Predicting benign jaw pathologies with nnU-Net deep learning model

BAYDAR O., GÜLŞEN İ. T., DİNÇ K., KURAN A., ÇELİK Ö., BAYRAKDAR İ. Ş., et al.

FDI 2024 WORLD DENTAL CONGRESS, İstanbul, Türkiye, 12 - 15 Eylül 2024, cilt.74, ss.10, (Özet Bildiri) Sürdürülebilir Kalkınma

Sürdürülebilir Kalkınma

4. MEASUREMENT OF AORTIC ROOT DIAMETER IN COMPARISON WITH EMERGENCY ECHOCARDIOGRAPHY AND COMPUTED TOMOGRAPHY, AND TESTING WITH MACHINE LEARNING

ŞEVİK Ö. E., ACAR N., ÇELİK Ö., ÇANAKÇI M. E., AY Y., AYDIN N., et al.

9th Eurasian Congress of Emergency Medicine, Antalya, Türkiye, 9 - 12 Kasım 2023, (Tam Metin Bildiri)

5. Annelerin İlk 6 Ay Sadece Anne Sütü Verme Durumlarının Makine Öğrenimi Tekniği İle Tahminlemesi

AÇIKGÖZ A., ÇAKIRLI M., MIZRAK ŞAHİN B., ÇELİK Ö.

4. Uluslararası Akdeniz Pediatri Hemşireliği ve 3. Uluslararası 8. Ulusal Pediatri Hemşireliği Kongresi, Erzurum, Türkiye, 01 Haziran 2023, (Özet Bildiri)

6. The Effect of In -Service Training Structured According To Gagne's Nine Teaching 45 Events on the Knowledge Level of Nurses

ÖZKARAMAN A., KERSU Ö., UZGÖR F., ÇAKIRLI M., ÇELİK Ö., Danacı B., et al.

World Congress on Advanced Nursing and Nursing Practice (WCANNP-23), Roma, İtalya, 07 Nisan 2023, ss.45, (Özet Bildiri)

7. Education Material for Nurses: Application of Smart Telephone

ÖZKARAMAN A., KERSU Ö., UZGÖR F., ÇAKIRLI M., ÇELİK Ö., Danacı B., et al.

World Congress on Advanced Nursing and Nursing Practice (WCANNP-23), Roma, İtalya, 07 Nisan 2023, ss.46, (Özet Bildiri)

8. Decision Making with Machine Learning in Emergency Department

Çanakçı M. E., Çelik Ö., Acar N.

8th Eurasian Congress on Emergency Medicine & 18th Turkish Congress on Emergency Medicine & 17th WINFOCUS World Congress, Antalya, Türkiye, 01 Aralık 2022, ss.420-421, (Tam Metin Bildiri) Sürdürülebilir Kalkınma

Sürdürülebilir Kalkınma

9. BITEWING RADYOGRAFİLERDE OTOMATİK DERİN ÖĞRENME İLE PULPA TAŞLARININ TESPİTİ: BİR YAPAY ZEKÂ PİLOT ÇALIŞMASI

Altındağ A., Uzun S., Bayrakdar İ. Ş., Çelik Ö.

4th International Congress of Maxillofacial Radiology Society 'Multidisciplinary Approach to Maxillofacial Imaging', İzmir, Türkiye, 19 - 23 Ekim 2022, ss.202-203, (Özet Bildiri)

10. How to improve the image recognitiob by a better annotation of a medical imagge in an artificial intellience

TOKAR B., ÇELİK Ö., ÇETİN N., Abbasov T., AK SİVRİKOZ İ.

12th ANNUAL CONGRESS of the EUROPEAN SOCIETY OF PAEDIATRIC ENDOSCOPIC SURGEONS, Barcelona, İspanya, 28 Eylül 2022, (Özet Bildiri)

11. PREDICTION OF ACUTE HEMATOLOGIC TOXICITY ASSOCIATED WITH RADIOTHERAPY IN RECTUM CANCER WITH ARTIFICIAL INTELLIGENCE

YAKAR M. Ç., ETİZ D., ÇELİK Ö., KÜTRİ D., ÖZEN A.

11. IGICC, İstanbul, Türkiye, 02 Aralık 2021, ss.10-11, (Özet Bildiri)

12. A deep learning algorithm for classification of oral lichenoid lesions from photographic images: A retrospective study

KESER G., BAYRAKDAR İ. Ş., NAMDAR PEKİNER F. M., ÇELİK Ö., ORHAN K.

15th Biennial Congress of European Association of Oral Medicine, Porto, Portekiz, 24 Eylül 2021, (Özet Bildiri)

13. TEXT CLASSIFICATION STUDY WITH SMS DATA

ÇELİK Ö., KAPLAN G.

HEZARFEN International Congress of Science, Mathematics and Engineering Sciences, İzmir, Türkiye, 08 Kasım 2019, (Özet Bildiri)

14. GENDER ANALYSIS IN SOCIAL MEDIA USING MACHINE LEARNING TECHNIQUES

ÇELİK Ö., ASLAN A. F.

International Conference on Advances in Science Technology, Punjab, Hindistan, 16 Mart 2018, (Özet Bildiri)

Metrikler

Yayın

113

Yayın (WoS)

64

Yayın (Scopus)

66

Atıf (WoS)

665

H-İndeks (WoS)

14

Atıf (Scopus)

948

H-İndeks (Scopus)

17

Atıf (Scholar)

627

H-İndeks (Scholar)

13

Atıf (TrDizin)

1

H-İndeks (TrDizin)

1

Atıf (Sobiad)

1

H-İndeks (Sobiad)

1

Atıf (Diğer Toplam)

1

Proje

7

Fikri Mülkiyet

2

Açık Erişim

17

BM Sürdürülebilir Kalkınma Amaçları