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Ghori, Khawaja Waqas Ur Rehman (2024) Multimodal Deep Learning for Lungs Cancer Detection: Integrating Audio and Image Analysis with Web-Based Accessibility. Masters thesis, Dublin, National College of Ireland.
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Abstract
Early detection of lung cancer and other respiratory diseases is a major global health challenge. This study investigates the integration of combination of both chest radiography and lung sounds into an accessible web-based platform for early detection of lung cancer. We present a multimodal deep learning approach that combines convolutional neural networks (CNNs) for image analysis and a gated regression unit (GRU) for sound processing. The question remains whether combining visual and audio data with advanced AI models and Application access can significantly improve early detection of lung cancer.
Our system has shown promise in early detection of lung diseases, including pre-cancerous lesions. Combining radiography and audiometric data significantly improves detection sensitivity compared to single-modality methods. Network integration of these AI models significantly reduces the diagnosis time and associated costs compared to traditional methods.
In addition, this study explores the broader implications of automating healthcare systems using AI and web technologies. Our results show that such integration significantly reduces human error, simplifies workflow, and democratizes access to advanced diagnostic tools. AI research will not only improve healthcare but also create the way for more effective, accurate, and affordable respiratory screening methods that could revolutionize early detection and treatment of lung cancer.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Zahoor, Sheresh UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Life sciences > Medical sciences > Pathology > Tumors > Cancer R Medicine > Healthcare Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning H Social Sciences > HM Sociology > Information Science > Communication > Medical Informatics |
| Divisions: | School of Computing > Master of Science in Artificial Intelligence |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 18 Jun 2025 11:43 |
| Last Modified: | 18 Jun 2025 11:43 |
| URI: | https://norma.ncirl.ie/id/eprint/7911 |
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