AI Radiologist: Reaching Clinical Consensus Using Structured Deep Learning

Buraque Sayed; Aliza Memon; Muhammad Haseeb; Rabail Bhatti; Shamshad Lakho

Authors

Buraque Sayed Computer Science Quest Nawabsha Hyderabad, Pakistan
Aliza Memon Computer Science Quest Nawabsha Hyderabad, Pakistan
Muhammad Haseeb Computer Science Quest Nawabshah, Pakistan
Rabail Bhatti Information Technology Quest Nawabshah, Nawabshah, Pakistan
Shamshad Lakho Computer Science Quest Nawabshah, Pakistan

Keywords:

Artificial Intelligence, Clinical Decision Support System (CDSS), Convolutional Neural Networks (CNN), Deep Learning, Medical Imaging, Retrieval-Augmented Generation (RAG)

Abstract

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References

Ke Song, Jing Feng, “A survey on deep learning in medical ultrasound imaging,” Front. Phys., vol. 2, no. 7, 2024.

Iryna Hartsock, Ghulam Rasool, “Vision-Language Models for Medical Report Generation and Visual Question Answering: A Review,” arXiv:2403.02469, 2024, [Online]. Available: https://arxiv.org/abs/2403.02469

Y. W. Chen, L. Lin, and R. K. Jain, “Recent Advances in Deep Learning for Medical Image Analysis: Paradigms and Applications,” Intell. Syst. Ref. Libr., vol. 278, pp. 1–274, 2026, doi: 10.1007/978-3-031-94791-9.

Ha Q. Nguyen, Khanh Lam, “VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations,” Sci. Data, vol. 9, 2022, [Online]. Available: https://www.nature.com/articles/s41597-022-01498-w

S. J. Raheel Siddiqi, “Deep Learning for Pneumonia Detection in Chest X-ray Images: A Comprehensive Survey,” J. Imaging, vol. 10, no. 8, p. 176, 2024, [Online]. Available: https://www.mdpi.com/2313-433X/10/8/176

S. K. Zhou et al., “A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies with Progress Highlights, and Future Promises,” Proc. IEEE, vol. 109, no. 5, pp. 820–838, May 2021, doi: 10.1109/JPROC.2021.3054390.