[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

BHM Van der Velden, HJ Kuijf, KGA Gilhuijs… - Medical Image …, 2022 - Elsevier
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …

Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT

L Li, L Qin, Z Xu, Y Yin, X Wang, B Kong, J Bai… - …, 2020 - pmc.ncbi.nlm.nih.gov
Background Coronavirus disease has widely spread all over the world since the beginning
of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest …

Using artificial intelligence to detect COVID-19 and community-acquired pneumonia based on pulmonary CT: evaluation of the diagnostic accuracy

L Li, L Qin, Z Xu, Y Yin, X Wang, B Kong, J Bai, Y Lu… - Radiology, 2020 - pubs.rsna.org
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world
since the beginning of 2020. It is desirable to develop automatic and accurate detection of …

Machine learning in action: stroke diagnosis and outcome prediction

S Mainali, ME Darsie, KS Smetana - Frontiers in neurology, 2021 - frontiersin.org
The application of machine learning has rapidly evolved in medicine over the past decade.
In stroke, commercially available machine learning algorithms have already been …

Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images

D Sharifrazi, R Alizadehsani, M Roshanzamir… - … Signal Processing and …, 2021 - Elsevier
Abstract The coronavirus (COVID-19) is currently the most common contagious disease
which is prevalent all over the world. The main challenge of this disease is the primary …

Advances in deep learning-based medical image analysis

X Liu, K Gao, B Liu, C Pan, K Liang, L Yan… - Health Data …, 2021 - spj.science.org
Importance. With the booming growth of artificial intelligence (AI), especially the recent
advancements of deep learning, utilizing advanced deep learning-based methods for …

Intracranial hemorrhage segmentation using a deep convolutional model

MD Hssayeni, MS Croock, AD Salman, HF Al-Khafaji… - Data, 2020 - mdpi.com
Traumatic brain injuries may cause intracranial hemorrhages (ICH). ICH could lead to
disability or death if it is not accurately diagnosed and treated in a time-sensitive procedure …

[HTML][HTML] A deep learning algorithm for automatic detection and classification of acute intracranial hemorrhages in head CT scans

X Wang, T Shen, S Yang, J Lan, Y Xu, M Wang… - NeuroImage: Clinical, 2021 - Elsevier
Acute Intracranial hemorrhage (ICH) is a life-threatening disease that requires emergency
medical attention, which is routinely diagnosed using non-contrast head CT imaging. The …

Multi-view feature fusion based four views model for mammogram classification using convolutional neural network

HN Khan, AR Shahid, B Raza, AH Dar… - IEEE Access, 2019 - ieeexplore.ieee.org
Breast cancer is the second most common cause of cancer-related deaths among women.
Early detection leads to better prognosis and saves lives. The 5-year survival rate of breast …