Artificial intelligence in lung cancer diagnosis and prognosis: Current application and future perspective

S Huang, J Yang, N Shen, Q Xu, Q Zhao - Seminars in Cancer Biology, 2023 - Elsevier
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the
world. The overall five-year survival rate of lung cancer is relatively lower than many leading …

[HTML][HTML] Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey

S Tomassini, N Falcionelli, P Sernani, L Burattini… - Computers in Biology …, 2022 - Elsevier
Lung cancer is among the deadliest cancers. Besides lung nodule classification and
diagnosis, developing non-invasive systems to classify lung cancer histological …

A two-stage convolutional neural networks for lung nodule detection

H Cao, H Liu, E Song, G Ma, X Xu, R Jin… - IEEE journal of …, 2020 - ieeexplore.ieee.org
Early detection of lung cancer is an effective way to improve the survival rate of patients. It is
a critical step to have accurate detection of lung nodules in computed tomography (CT) …

On the performance of lung nodule detection, segmentation and classification

D Gu, G Liu, Z Xue - Computerized Medical Imaging and Graphics, 2021 - Elsevier
Computed tomography (CT) screening is an effective way for early detection of lung cancer
in order to improve the survival rate of such a deadly disease. For more than two decades …

[HTML][HTML] Survey on deep learning for pulmonary medical imaging

J Ma, Y Song, X Tian, Y Hua, R Zhang, J Wu - Frontiers of medicine, 2020 - Springer
As a promising method in artificial intelligence, deep learning has been proven successful in
several domains ranging from acoustics and images to natural language processing. With …

Automatic nodule detection for lung cancer in CT images: A review

G Zhang, S Jiang, Z Yang, L Gong, X Ma, Z Zhou… - Computers in biology …, 2018 - Elsevier
Automatic lung nodule detection has great significance for treating lung cancer and
increasing patient survival. This work summarizes a critical review of recent techniques for …

Detection and classification of pulmonary nodules using convolutional neural networks: a survey

P Monkam, S Qi, H Ma, W Gao, Y Yao, W Qian - Ieee Access, 2019 - ieeexplore.ieee.org
CT screening has been proven to be effective for diagnosing lung cancer at its early
manifestation in the form of pulmonary nodules, thus decreasing the mortality. However, the …

A deep CNN based transfer learning method for false positive reduction

Z Shi, H Hao, M Zhao, Y Feng, L He, Y Wang… - Multimedia Tools and …, 2019 - Springer
A low false positive (FP) rate is of great importance for the use of a Computer Aided
Detection (CAD) system to detect pulmonary nodules in thoracic Computed Tomography …

Stbi-yolo: A real-time object detection method for lung nodule recognition

K Liu - IEEE Access, 2022 - ieeexplore.ieee.org
Lung cancer is the most prevalent and deadly oncological disease in the world, but a timely
detection of lung nodules can greatly improve the survival rate of this disease. However, due …

[HTML][HTML] The effects of artificial intelligence assistance on the radiologists' assessment of lung nodules on CT scans: a systematic review

LJS Ewals, K van der Wulp… - Journal of clinical …, 2023 - mdpi.com
To reduce the number of missed or misdiagnosed lung nodules on CT scans by radiologists,
many Artificial Intelligence (AI) algorithms have been developed. Some algorithms are …