A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …
Deep learning in radiology for lung cancer diagnostics: A systematic review of classification, segmentation, and predictive modeling techniques
This study presents a comprehensive systematic review focusing on the applications of deep
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
learning techniques in lung cancer radiomics. Through a rigorous screening process of 589 …
An effective method for lung cancer diagnosis from ct scan using deep learning-based support vector network
Simple Summary This study provides an efficient method for lung cancer diagnosis from
computed tomography images and employs deep learning-supported support vector …
computed tomography images and employs deep learning-supported support vector …
[PDF][PDF] End-to-end data authentication deep learning model for securing IoT configurations
Compared to other biometrics, electrocardiograms (ECGs) have gained widespread
acceptability as mediums for validating animateness in numerous security applications …
acceptability as mediums for validating animateness in numerous security applications …
[HTML][HTML] AI applications in robotics, diagnostic image analysis and precision medicine: Current limitations, future trends, guidelines on CAD systems for medicine
Background AI in healthcare has been recognized by both academia and industry in
revolutionizing how healthcare services will be offered by healthcare service providers and …
revolutionizing how healthcare services will be offered by healthcare service providers and …
Towards machine learning-aided lung cancer clinical routines: Approaches and open challenges
Advancements in the development of computer-aided decision (CAD) systems for clinical
routines provide unquestionable benefits in connecting human medical expertise with …
routines provide unquestionable benefits in connecting human medical expertise with …
Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm
Lung cancer detection has become one of the most challenging oncology problems. It is an
arduous task for radiologists to detect nodules based on the naked eye vision. The main …
arduous task for radiologists to detect nodules based on the naked eye vision. The main …
Ensemble framework based on attributes and deep features for benign-malignant classification of lung nodule
J Qiao, Y Fan, M Zhang, K Fang, D Li… - … Signal Processing and …, 2023 - Elsevier
Early detection and identification of malignant lung nodules improve the survival of lung
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …
cancer patients. The visual attributes such as subtlety, spiculation, and calcification of lung …
Reliable object recognition using deep transfer learning for marine transportation systems with underwater surveillance
In recent years, object recognition for marine persistent surveillance has attracted much
attention from researchers. The surveillance videos are captured with using optical sensors …
attention from researchers. The surveillance videos are captured with using optical sensors …