Timedistributed-cnn-lstm: A hybrid approach combining cnn and lstm to classify brain tumor on 3d mri scans performing ablation study
Identification of brain tumors at an early stage is crucial in cancer diagnosis, as a timely
diagnosis can increase the chances of survival. Considering the challenges of tumor …
diagnosis can increase the chances of survival. Considering the challenges of tumor …
A survey on AI techniques for thoracic diseases diagnosis using medical images
Thoracic diseases refer to disorders that affect the lungs, heart, and other parts of the rib
cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis …
cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis …
[HTML][HTML] Application of various yolo models for computer vision-based real-time pothole detection
Pothole repair is one of the paramount tasks in road maintenance. Effective road surface
monitoring is an ongoing challenge to the management agency. The current pothole …
monitoring is an ongoing challenge to the management agency. The current pothole …
Artificial intelligence in COPD CT images: identification, staging, and quantitation
Chronic obstructive pulmonary disease (COPD) stands as a significant global health
challenge, with its intricate pathophysiological manifestations often demanding advanced …
challenge, with its intricate pathophysiological manifestations often demanding advanced …
Radiomics for improved detection of chronic obstructive pulmonary disease in low-dose and standard-dose chest CT scans
Background Approximately half of adults with chronic obstructive pulmonary disease
(COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice …
(COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice …
An unsupervised image registration method employing chest computed tomography images and deep neural networks
Background Deformable image registration is crucial for multiple radiation therapy
applications. Fast registration of computed tomography (CT) lung images is challenging …
applications. Fast registration of computed tomography (CT) lung images is challenging …
A novel melspectrogram snippet representation learning framework for severity detection of chronic obstructive pulmonary diseases
A chronic obstructive pulmonary disease (COPD) is a major public health concern across
the world. Since it is an incurable disease, early detection and accurate diagnosis are very …
the world. Since it is an incurable disease, early detection and accurate diagnosis are very …
MCLSG: Multi-modal classification of lung disease and severity grading framework using consolidated feature engineering mechanisms
AMQ Farhan, S Yang, AQS Al-Malahi… - … Signal Processing and …, 2023 - Elsevier
Human disease detection using medical images with algorithmic severity prediction is
unexplored. Deep learning algorithms for disease identification and classification from …
unexplored. Deep learning algorithms for disease identification and classification from …
A cloud-based deep learning model in heterogeneous data integration system for lung cancer detection in medical industry 4.0
Currently, lung cancer has become one of the most common and deadliest types of cancer.
Due to its severity, many countries are now encouraging their at-risk citizens to test and treat …
Due to its severity, many countries are now encouraging their at-risk citizens to test and treat …
Early detection of COPD based on graph convolutional network and small and weakly labeled data
Z Li, K Huang, L Liu, Z Zhang - Medical & Biological Engineering & …, 2022 - Springer
Chronic obstructive pulmonary disease (COPD) is a common disease with high morbidity
and mortality, where early detection benefits the population. However, the early diagnosis …
and mortality, where early detection benefits the population. However, the early diagnosis …