Explainable deep learning methods in medical image classification: A survey
The remarkable success of deep learning has prompted interest in its application to medical
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
imaging diagnosis. Even though state-of-the-art deep learning models have achieved …
Automatic captioning for medical imaging (MIC): a rapid review of literature
Automatically understanding the content of medical images and delivering accurate
descriptions is an emerging field of artificial intelligence that combines skills in both …
descriptions is an emerging field of artificial intelligence that combines skills in both …
Deep learning approaches on image captioning: A review
Image captioning is a research area of immense importance, aiming to generate natural
language descriptions for visual content in the form of still images. The advent of deep …
language descriptions for visual content in the form of still images. The advent of deep …
Measuring representational harms in image captioning
Previous work has largely considered the fairness of image captioning systems through the
underspecified lens of “bias.” In contrast, we present a set of techniques for measuring five …
underspecified lens of “bias.” In contrast, we present a set of techniques for measuring five …
[HTML][HTML] Improving chest X-ray report generation by leveraging warm starting
Automatically generating a report from a patient's Chest X-rays (CXRs) is a promising
solution to reducing clinical workload and improving patient care. However, current CXR …
solution to reducing clinical workload and improving patient care. However, current CXR …
Deep image captioning: A review of methods, trends and future challenges
Image captioning, also called report generation in medical field, aims to describe visual
content of images in human language, which requires to model semantic relationship …
content of images in human language, which requires to model semantic relationship …
[HTML][HTML] Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies
W Hryniewska, P Bombiński, P Szatkowski… - Pattern Recognition, 2021 - Elsevier
The sudden outbreak and uncontrolled spread of COVID-19 disease is one of the most
important global problems today. In a short period of time, it has led to the development of …
important global problems today. In a short period of time, it has led to the development of …
Combining the transformer and convolution for effective brain tumor classification using MRI images
In the world, brain tumor (BT) is considered the major cause of death related to cancer,
which requires early and accurate detection for patient survival. In the early detection of BT …
which requires early and accurate detection for patient survival. In the early detection of BT …
Viral reverse engineering using Artificial Intelligence and big data COVID-19 infection with Long Short-term Memory (LSTM)
This research presents a reverse engineering approach to discover the patterns and
evolution behavior of SARS-CoV-2 using AI and big data. Accordingly, we have studied five …
evolution behavior of SARS-CoV-2 using AI and big data. Accordingly, we have studied five …
Diagnosis of ulcerative colitis from endoscopic images based on deep learning
X Luo, J Zhang, Z Li, R Yang - Biomedical Signal Processing and Control, 2022 - Elsevier
Aims Evaluating the endoscopic images of patients with ulcerative colitis can effectively
determine a reasonable treatment plan. However, the endoscopic evaluation is usually …
determine a reasonable treatment plan. However, the endoscopic evaluation is usually …