Diagnostics, Volume 13, Issue 1
2023 January-1 - 168 articles
Cover Story: Chest X-ray (CXR) is among the most frequently used medical imaging modalities by Radiologists and Physicians. It has a preeminent value in the detection of multiple life-threatening diseases. Most thoracic diseases have similar patterns, which makes diagnosis prone to human error. Deep learning (DL) provides techniques to make this task more efficient. This work reviews recent advances in DL for CXR disease detection. We present the developed algorithms, the preprocessing techniques and the available datasets. We discuss the challenges present in the published literature and highlight the importance of interpretability and explainability to better understand the models’ detections. Finally, we outline a direction for researchers to help develop more effective models for the early detection of chest diseases. View this paper - Issues are regarded as officially published after their release is announced to the table of contents alert mailing list .
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