A comprehensive review of deep learning in colon cancer. - Ishak Paçal; Dervis Karaboga; Alper Bastürk; Bahriye Akay; Özkan Ufuk Nalbantoglu (Comput. Biol. Medicine, 2020)

A robust real-time deep learning based automatic polyp detection system. - Ishak Paçal; Dervis Karaboga (Comput. Biol. Medicine, 2021)

An efficient real-time colonic polyp detection with YOLO algorithms trained by using negative samples and large datasets. - Ishak Paçal; Ahmet Karaman; Dervis Karaboga; Bahriye Akay; Alper Bastürk; Özkan Ufuk Nalbantoglu; Seymanur Coskun (Comput. Biol. Medicine, 2022)

Derin öğrenme tabanlı gerçek zamanlı polip tespit yöntemlerinin geliştirilmesi ve incelenmesi (Development and investigation of deep learning based real-time polyp detection methods) - Ishak Paçal (2022)

Evaluation of Deep Learning Models in Search by Example using Capsule Endoscopy Images. - Rodrigo Fernandes; Alexandre Pessoa 001; José Nogueira; Anselmo Cardoso de Paiva; Ishak Paçal; Marta Salgado; António Cunha (CENTERIS/ProjMAN/HCist, 2023)

Hyper-parameter optimization of deep learning architectures using artificial bee colony (ABC) algorithm for high performance real-time automatic colorectal cancer (CRC) polyp detection. - Ahmet Karaman; Dervis Karaboga; Ishak Paçal; Bahriye Akay; Alper Bastürk; Özkan Ufuk Nalbantoglu; Seymanur Coskun; Omur Sahin (Appl. Intell., 2023)

Robust real-time polyp detection system design based on YOLO algorithms by optimizing activation functions and hyper-parameters with artificial bee colony (ABC). - Ahmet Karaman; Ishak Paçal; Alper Bastürk; Bahriye Akay; Özkan Ufuk Nalbantoglu; Seymanur Coskun; Omur Sahin; Dervis Karaboga (Expert Syst. Appl., 2023)

Deep learning-based approaches for robust classification of cervical cancer. - Ishak Paçal; Serhat Kiliçarslan (Neural Comput. Appl., 2023)

A comparative study of YOLO models and a transformer-based YOLOv5 model for mass detection in mammograms. - Damla Coskun; Dervis Karaboga; Alper Bastürk; Bahriye Akay; Özkan Ufuk Nalbantoglu; Serap Dogan; Ishak Paçal; Meryem Altin Karagöz (Turkish J. Electr. Eng. Comput. Sci., 2023)

A Deep Learning Approach to Annotating Endoscopic Capsule Videos via CBIR. - Inês Castro Fernandes; Rodrigo Fernandes; Alexandre Pessoa 001; Marta Salgado; Anselmo Cardoso de Paiva; Ishak Paçal; António Cunha (CENTERIS/ProjMAN/HCist, 2024)

Enhancing Image Annotation With Object Tracking and Image Retrieval: A Systematic Review. - Rodrigo Fernandes; Alexandre Pessoa 001; Marta Salgado; Anselmo Cardoso de Paiva; Ishak Paçal; António Cunha (IEEE Access, 2024)

MaxCerVixT: A novel lightweight vision transformer-based Approach for precise cervical cancer detection. - Ishak Paçal (Knowl. Based Syst., 2024)

Enhancing crop productivity and sustainability through disease identification in maize leaves: Exploiting a large dataset with an advanced vision transformer model. - Ishak Paçal (Expert Syst. Appl., 2024)

Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review. - Mohammed Lubbad; Dervis Karaboga; Alper Bastürk; Bahriye Akay; Özkan U. Nalbantoglu; Ishak Paçal (Neural Comput. Appl., 2024)

Real-time sign language recognition based on YOLO algorithm. - Melek Alaftekin; Ishak Paçal; Kenan Cicek (Neural Comput. Appl., 2024)

Few-shot classification of ultrasound breast cancer images using meta-learning algorithms. - Gültekin Isik; Ishak Paçal (Neural Comput. Appl., 2024)

A novel Swin transformer approach utilizing residual multi-layer perceptron for diagnosing brain tumors in MRI images. - Ishak Paçal (Int. J. Mach. Learn. Cybern., 2024)

A systematic review of deep learning techniques for plant diseases. - Ishak Paçal; Ismail Kunduracioglu; Mehmet Hakki Alma; Muhammet Deveci; Seifedine Nimer Kadry; Jan Nedoma; Vlastimil Slany; Radek Martinek (Artif. Intell. Rev., 2024)

Enhancing EfficientNetv2 with global and efficient channel attention mechanisms for accurate MRI-Based brain tumor classification. - Ishak Paçal; Omer Celik; Bilal Bayram; António Cunha (Clust. Comput., 2024)

Attention Enhanced InceptionNeXt-Based Hybrid Deep Learning Model for Lung Cancer Detection. - Burhanettin Ozdemir; Emrah Aslan; Ishak Paçal (IEEE Access, 2025)

InceptionNeXt-Transformer: A novel multi-scale deep feature learning architecture for multimodal breast cancer diagnosis. - Ishak Paçal; Omneya Attallah (Biomed. Signal Process. Control., 2025)

A novel CNN-ViT-based deep learning model for early skin cancer diagnosis. - Ishak Paçal; Burhanettin Ozdemir; Javanshir Zeynalov; Huseyn Gasimov; Nurettin Pacal (Biomed. Signal Process. Control., 2025)

A novel hybrid ConvNeXt-based approach for enhanced skin lesion classification. - Ibrahim Aruk; Ishak Paçal; Ahmet Nusret Toprak (Expert Syst. Appl., 2025)

Hybrid deep learning model for automated colorectal cancer detection using local and global feature extraction. - Ishak Paçal; Omneya Attallah (Knowl. Based Syst., 2025)

Utilizing convolutional neural networks and vision transformers for precise corn leaf disease identification. - Ishak Paçal; Gültekin Isik (Neural Comput. Appl., 2025)

Efficient and autonomous detection of olive leaf diseases using AI-enhanced MetaFormer. - Ishak Paçal; Serhat Kiliçarslan; Burhanettin Ozdemir; Muhammet Deveci; Seifedine Kadry 001 (Artif. Intell. Rev., 2025)