Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives

J Li, J Chen, Y Tang, C Wang, BA Landman… - Medical image …, 2023 - Elsevier
Transformer, one of the latest technological advances of deep learning, has gained
prevalence in natural language processing or computer vision. Since medical imaging bear …

A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning

Y Gu, J Chi, J Liu, L Yang, B Zhang, D Yu… - Computers in biology …, 2021 - Elsevier
Lung cancer has one of the highest mortalities of all cancers. According to the National Lung
Screening Trial, patients who underwent low-dose computed tomography (CT) scanning …

Application of artificial intelligence in lung cancer

HY Chiu, HS Chao, YM Chen - Cancers, 2022 - mdpi.com
Simple Summary Lung cancer is the leading cause of malignancy-related mortality
worldwide. AI has the potential to help to treat lung cancer from detection, diagnosis and …

Deep learning for medical image-based cancer diagnosis

X Jiang, Z Hu, S Wang, Y Zhang - Cancers, 2023 - mdpi.com
Simple Summary Deep learning has succeeded greatly in medical image-based cancer
diagnosis. To help readers better understand the current research status and ideas, this …

Pre-training in medical data: A survey

Y Qiu, F Lin, W Chen, M Xu - Machine Intelligence Research, 2023 - Springer
Medical data refers to health-related information associated with regular patient care or as
part of a clinical trial program. There are many categories of such data, such as clinical …

Self-supervised learning of neighborhood embedding for longitudinal MRI

J Ouyang, Q Zhao, E Adeli, G Zaharchuk… - Medical image analysis, 2022 - Elsevier
In recent years, several deep learning models recommend first to represent Magnetic
Resonance Imaging (MRI) as latent features before performing a downstream task of interest …

A comprehensive review of computer-aided diagnosis of pulmonary nodules based on computed tomography scans

W Cao, R Wu, G Cao, Z He - IEEE Access, 2020 - ieeexplore.ieee.org
Lung cancer is one of the malignant tumor diseases with the fastest increase in morbidity
and mortality, which poses a great threat to human health. Low-Dose Computed …

Multi-modal evolutionary deep learning model for ovarian cancer diagnosis

RM Ghoniem, AD Algarni, B Refky, AA Ewees - Symmetry, 2021 - mdpi.com
Ovarian cancer (OC) is a common reason for mortality among women. Deep learning has
recently proven better performance in predicting OC stages and subtypes. However, most of …

Ovary cancer diagnosing empowered with machine learning

N Taleb, S Mehmood, M Zubair, I Naseer… - … for Technology and …, 2022 - ieeexplore.ieee.org
A high mortality rate is associated with ovarian cancer, one of the most common types of
cancers in women. Ovarian cancer refers to a group of disorders that develop in the ovaries …

Time-distanced gates in long short-term memory networks

R Gao, Y Tang, K Xu, Y Huo, S Bao, SL Antic… - Medical image …, 2020 - Elsevier
Abstract The Long Short-Term Memory (LSTM) network is widely used in modeling
sequential observations in fields ranging from natural language processing to medical …