Telegram chatbot for lung cancer diagnosis based on an adaptive combination algorithm using a deep learning model
Zainab K. Abbas1, Mustafa Raad Mutashar1 and Fatima M. Sadiq1
College of Business Informatics,College of Business Informatics, University of Information Technology and Communications, Baghdad,Iraq1
Corresponding Author : Zainab K. Abbas
Recieved : 04-July-2025; Revised : 15-September-2025; Accepted : 18-September-2025
Abstract
Lung cancer is one of the deadliest types of cancer and has affected thousands of individuals in recent years. Patients have a very low chance of survival if the disease is not diagnosed at an early stage. Early detection can help save the patient’s life and enable simpler, more effective treatment. To facilitate timely diagnosis and recovery, an automated lung cancer detection system is required, and artificial intelligence (AI) can play a key role in addressing this need. In this work, an intelligent system based on a combination of a transfer learning model (ResNet50) and a deep classifier was proposed. The model was trained on the “IQ-OTH/NCCD” dataset and achieved a testing accuracy of up to 98.18%. For practical use, medical images can be submitted through a user interface implemented on the Telegram messaging platform, where the model processes the input and returns classification results in real time. Since the model was trained on a specific dataset, the experimental results demonstrate that it is effective in correctly classifying full lung images from that database.
Keywords
Lung cancer, Medical image classification, Deep learning, Transfer learning, ResNet50
Cite this article
Abbas ZK, Mutashar MR, Sadiq FM. Telegram chatbot for lung cancer diagnosis based on an adaptive combination algorithm using a deep learning model. International Journal of Advanced Computer Research. 2026;16(75):10-22. DOI : 10.19101/IJACR.2025.1570012
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