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Currently, gastrointestinal findings in medical diagnosis are primarily determined by manual inspection by competent gastrointestinal endoscopists. This evaluation procedure is labor-intensive, time-consuming, and frequently results in high variability between laboratories. To address these challenges, we introduced a specialized CNN-based architecture called GastroFuse-Net, designed to recognize human gastrointestinal diseases from endoscopic images. GastroFuse-Net was developed by combining features extracted from two different CNN models with different numbers of layers, integrating shallow and deep representations to capture diverse aspects of the abnormalities. The Kvasir dataset was used to thoroughly test the proposed deep learning model. This dataset contained images that were classified according to structures (cecum, z-line, pylorus), diseases (ulcerative colitis, esophagitis, polyps), or surgical operations (dyed resection margins, dyed lifted polyps). The proposed model was evaluated using various measures, including specificity, recall, precision, F1-score, Mathew's Correlation Coefficient (MCC), and accuracy. The proposed model GastroFuse-Net exhibited exceptional performance, achieving a precision of 0.985, recall of 0.985, specificity of 0.984, F1-score of 0.997, MCC of 0.982, and an accuracy of 98.5%.&lt;\/p&gt;<\/jats:p>","DOI":"10.3934\/mbe.2024300","type":"journal-article","created":{"date-parts":[[2024,8,16]],"date-time":"2024-08-16T06:22:46Z","timestamp":1723789366000},"page":"6847-6869","source":"Crossref","is-referenced-by-count":2,"title":["GastroFuse-Net: an ensemble deep learning framework designed for gastrointestinal abnormality detection in endoscopic images"],"prefix":"10.3934","volume":"21","author":[{"given":"Sonam","family":"Aggarwal","sequence":"first","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isha","family":"Gupta","sequence":"additional","affiliation":[{"name":"Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashok","family":"Kumar","sequence":"additional","affiliation":[{"name":"Model Institute of Engineering and Technology, Jammu, J&amp;K, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandeep","family":"Kautish","sequence":"additional","affiliation":[{"name":"Chandigarh University, Mohali, Punjab 140413 India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Abdulaziz S.","family":"Almazyad","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, College of Computer and Information Sciences, King Saud University, P.O. 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