プロフィール詳細

プロジェクトを作成

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Dr. Sevda G.に依頼

Turkey

Medical AI Systems Consultant | Robust Machine Learning & Image Analysis | PhD

プロフィール概要

Hi, I am a PhD-level researcher and consultant specializing in medical artificial intelligence, with a strong focus on predictive modeling and medical image analysis. I have hands-on experience developing classification and forecasting models using machine learning and deep learning, as well as building robust data preprocessing and validation pipelines. My work includes medical image processing, image restoration and filtering, anomaly detection, statistical analysis, and model performance evaluation. I have led multiple nationally funded research projects where I designed and validated AI systems intended for reliable real-world use. I help organizations develop, evaluate, and improve AI models for medical and health-related applications, with an emphasis on reliability, generalization, and practical deployment. I am available for consulting, model validation, medical image analysis, and predictive modeling projects, and I am comfortable working with both research teams and industry partners. Best regards

専門分野

• ☆ Data Analysis
• ☆ Image Processing
• ☆ Machine Learning
• ☆ Artificial Intelligence

サービス

• Consulting
• Data & AI

Consulting Scientific and Technical Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-ML, Data Mining, Data Cleaning, Data Processing, Data Insights

職務経験

Lecturar

Sakarya University

4月 2018 - 現在

Dr.

Sakarya Üniversitesi

4月 2018 - 現在

学歴

Electric and Elektronic Engineering

Sakarya University

9月 2017 - 7月 2021

Electric and Elektronic Engineering

Sakarya University

9月 2015 - 6月 2017

Electric and Elektronic Engineering

Sakarya University

9月 2014 - 6月 2015

Electronic Teaching

Sakarya University

9月 2008 - 6月 2012

認定資格

• 認定資格の詳細は未入力です。

出版物

CONFERENCE PAPER

SG-SAM: Segmentation of Challenging Skin Lesions with GroundingDino and SAM @inproceedings{_et_nel_2025, title={SG-SAM: Segmentation of Challenging Skin Lesions with GroundingDino and SAM}, url={http://dx.doi.org/10.1109/siu66497.2025.11112327}, DOI={10.1109/siu66497.2025.11112327}, booktitle={2025 33rd Signal Processing and Communications Applications Conference (SIU)}, publisher={IEEE}, author={Çetİnel, Gökçen and Aydin, Bekir Murat and Gül, Sevda}, year={2025}, month=jun, pages={1–4} } . 2025 33rd Signal Processing and Communications Applications Conference (SIU).

Sevda GÜL (2024). Skin lesion segmentation with semantic SAM: pros and cons . Selcuk University Journal of Engineering Sciences.

Breast Lesion Classification Based on Shape Features @inproceedings{Cetinel_2019, title={Breast Lesion Classification Based on Shape Features}, url={http://dx.doi.org/10.1109/siu.2019.8806388}, DOI={10.1109/siu.2019.8806388}, booktitle={2019 27th Signal Processing and Communications Applications Conference (SIU)}, publisher={IEEE}, author={Cetinel, Gokcen and Mutlu, Fuldem and Gul, Sevda}, year={2019}, month=apr, pages={1–4} } . 2019 27th Signal Processing and Communications Applications Conference (SIU).

Identification and grading of spasticity by using AdaBoost and k-NN techniques @inproceedings{Albayrak_2017, title={Identification and grading of spasticity by using AdaBoost and k-NN techniques}, url={http://dx.doi.org/10.1109/siu.2017.7960202}, DOI={10.1109/siu.2017.7960202}, booktitle={2017 25th Signal Processing and Communications Applications Conference (SIU)}, publisher={IEEE}, author={Albayrak, Yalcin and Cetinel, Gokcen and Gul, Sevda}, year={2017}, month=may, pages={1–4} } . 2017 25th Signal Processing and Communications Applications Conference (SIU).

An EOG based communication channel for paralyzed patients @inproceedings{Karagoz_2017, title={An EOG based communication channel for paralyzed patients}, url={http://dx.doi.org/10.1109/siu.2017.7960371}, DOI={10.1109/siu.2017.7960371}, booktitle={2017 25th Signal Processing and Communications Applications Conference (SIU)}, publisher={IEEE}, author={Karagoz, Yurdagul and Gul, Sevda and Cetinel, Gokcen}, year={2017}, month=may, pages={1–4} } . 2017 25th Signal Processing and Communications Applications Conference (SIU).

JOURNAL ARTICLE

YOLOSAMIC: A Hybrid Approach to Skin Cancer Segmentation with the Segment Anything Model and YOLOv8 @article{G_l_2025, title={YOLOSAMIC: A Hybrid Approach to Skin Cancer Segmentation with the Segment Anything Model and YOLOv8}, volume={15}, ISSN={2075-4418}, url={http://dx.doi.org/10.3390/diagnostics15040479}, DOI={10.3390/diagnostics15040479}, number={4}, journal={Diagnostics}, publisher={MDPI AG}, author={Gül, Sevda and Cetinel, Gökçen and Aydin, Bekir Murat and Akgün, Devrim and Öztaş Kara, Rabia}, year={2025}, month=feb, pages={479} } . Diagnostics.

(2025). YOLOSAMIC: A Hybrid Approach to Skin Cancer Segmentation with the Segment Anything Model and YOLOv8 . DIAGNOSTICS.

(2025). SG-SAM: Segmentation of Challenging Skin Lesions with GroundingDino and SAM . 2025 33RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, SIU.

Gökçen Çetinel, Bekir Murat Aydın, Sevda Gül, Devrim Akgün, Rabia Öztaş Kara (2024). An Evaluation of Skin Lesion Segmentation Using Deep Learning Architectures . Sakarya University Journal of Computer and Information Sciences.

Fuldem MUTLU, Sevda GÜL (2023). Improving the performance of EM and K-means algorithms for breast lesion segmentation . Anatolian Current Medical Journal.

Sevda G l Sevda G l, Aynur Manzak and G k en etinel Aynur Manzak and G k en etinel(2021). Prediction of Succinic Acid Extraction Efficiency in the Emulsion Liquid Membrane by using Machine Learning Techniques . Journal of the chemical society of pakistan. 43. (2). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 104–104. Chemical Society of Pakistan

(2021). Prediction of Succinic Acid Extraction Efficiency in the Emulsion Liquid Membrane by using Machine Learning Techniques. JOURNAL OF THE CHEMICAL SOCIETY OF PAKISTAN.

A fully-automated computer-aided breast lesion detection and classification system @article{Mutlu_2020, title={A fully-automated computer-aided breast lesion detection and classification system}, volume={62}, ISSN={1746-8094}, url={http://dx.doi.org/10.1016/j.bspc.2020.102157}, DOI={10.1016/j.bspc.2020.102157}, journal={Biomedical Signal Processing and Control}, publisher={Elsevier BV}, author={Mutlu, Fuldem and Çetinel, Gökçen and Gül, Sevda}, year={2020}, month=sep, pages={102157} } . Biomedical Signal Processing and Control.

Decision support system for breast lesions via dynamic contrast enhanced magnetic resonance imaging @article{_etinel_2020, title={Decision support system for breast lesions via dynamic contrast enhanced magnetic resonance imaging}, volume={43}, ISSN={2662-4737}, url={http://dx.doi.org/10.1007/s13246-020-00902-2}, DOI={10.1007/s13246-020-00902-2}, number={3}, journal={Physical and Engineering Sciences in Medicine}, publisher={Springer Science and Business Media LLC}, author={Çetinel, Gökçen and Mutlu, Fuldem and Gül, Sevda}, year={2020}, month=jul, pages={1029–1048} } . Physical and Engineering Sciences in Medicine.

Gökçen Çetinel, Fuldem Mutlu, Sevda Gül (2020). Detection of Breast Region of Interest via Breast MR Scan on an Axial Slice . International Journal of Applied Mathematics Electronics and Computers.

(2020). Decision support system for breast lesions via dynamic contrast enhanced magnetic resonance imaging . PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE.

(2020). A fully-automated computer-aided breast lesion detection and classification system . BIOMEDICAL SIGNAL PROCESSING AND CONTROL.

(2019). Breast Lesion Classification Based on Shape Features. 2019 27TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU).

Meme Manyetik Rezonans Görüntülemede Lezyon Sınırlarının ve Alanının Tespit Edilmesi @article{_ET_NEL_2018, title={Meme Manyetik Rezonans Görüntülemede Lezyon Sınırlarının ve Alanının Tespit Edilmesi}, volume={22}, ISSN={2147-835X}, url={http://dx.doi.org/10.16984/saufenbilder.322604}, DOI={10.16984/saufenbilder.322604}, number={1}, journal={Sakarya University Journal of Science}, publisher={Sakarya University Journal of Science}, author={ÇETİNEL, Gökçen and GÜL, Sevda}, year={2018}, month=feb, pages={108–127} } . Sakarya University Journal of Science.

Move Your Wheelchair with Your Eyes @article{_etinel_2017, title={Move Your Wheelchair with Your Eyes}, volume={1}, ISSN={2147-8228}, url={http://dx.doi.org/10.18100/ijamec.2017specialissue30462}, DOI={10.18100/ijamec.2017specialissue30462}, number={SpecialIssue}, journal={International Journal of Applied Mathematics, Electronics and Computers}, publisher={International Journal of Applied Mathematics, Electronics and Computers}, author={Çetinel, Gökçen and Gül, Sevda and Tiryaki, Zafer and Kuzu, Enes and Milligüney, Meltem}, year={2017}, month=aug, pages={5–8} } . International Journal of Applied Mathematics, Electronics and Computers.

(2017). An FOG Based Communication Channel for Paralyzed Patients. 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU).

(2017). Identification and Grading of Spasticity By Using AdaBoost and k-NN Techniques. 2017 25TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU).