[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 …

[HTML][HTML] Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks

S Nazir, DM Dickson, MU Akram - Computers in Biology and Medicine, 2023 - Elsevier
Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

Deep learning techniques to diagnose lung cancer

L Wang - Cancers, 2022 - mdpi.com
Simple Summary This study investigates the latest achievements, challenges, and future
research directions of deep learning techniques for lung cancer and pulmonary nodule …

Deep learning for computational cytology: A survey

H Jiang, Y Zhou, Y Lin, RCK Chan, J Liu, H Chen - Medical Image Analysis, 2023 - Elsevier
Computational cytology is a critical, rapid-developing, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …

Deep convolutional neural network-based classification of cancer cells on cytological pleural effusion images

X Xie, CC Fu, L Lv, Q Ye, Y Yu, Q Fang, L Zhang… - Modern …, 2022 - nature.com
Lung cancer is one of the leading causes of cancer-related death worldwide. Cytology plays
an important role in the initial evaluation and diagnosis of patients with lung cancer …

ISANET: Non-small cell lung cancer classification and detection based on CNN and attention mechanism

Z Xu, H Ren, W Zhou, Z Liu - Biomedical Signal Processing and Control, 2022 - Elsevier
Lung cancer is one of the malignant tumors with high morbidity and mortality worldwide.
Among them, non-small cell lung cancer accounts for about 85% of all lung cancers. In the …

Deep learning approach to classification of lung cytological images: Two-step training using actual and synthesized images by progressive growing of generative …

A Teramoto, T Tsukamoto, A Yamada, Y Kiriyama… - PloS one, 2020 - journals.plos.org
Cytology is the first pathological examination performed in the diagnosis of lung cancer. In
our previous study, we introduced a deep convolutional neural network (DCNN) to …

A survey of computer-aided tumor diagnosis based on convolutional neural network

Y Yan, XJ Yao, SH Wang, YD Zhang - Biology, 2021 - mdpi.com
Simple Summary One of the hottest areas in deep learning is computerized tumor diagnosis
and treatment. The identification of tumor markers, the outline of tumor growth activity, and …

Automated detection and segmentation of early gastric cancer from endoscopic images using mask R-CNN

T Shibata, A Teramoto, H Yamada, N Ohmiya, K Saito… - Applied Sciences, 2020 - mdpi.com
Gastrointestinal endoscopy is widely conducted for the early detection of gastric cancer.
However, it is often difficult to detect early gastric cancer lesions and accurately evaluate the …

A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications

H Hashemzadeh, S Shojaeilangari, A Allahverdi… - Scientific reports, 2021 - nature.com
Lung cancer is a leading cause of cancer death in both men and women worldwide. The
high mortality rate in lung cancer is in part due to late-stage diagnostics as well as spread of …