Transfer learning techniques for medical image analysis: A review
Medical imaging is a useful tool for disease detection and diagnostic imaging technology
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
has enabled early diagnosis of medical conditions. Manual image analysis methods are …
Recent advancement in cancer diagnosis using machine learning and deep learning techniques: A comprehensive review
D Painuli, S Bhardwaj - Computers in Biology and Medicine, 2022 - Elsevier
Being a second most cause of mortality worldwide, cancer has been identified as a perilous
disease for human beings, where advance stage diagnosis may not help much in …
disease for human beings, where advance stage diagnosis may not help much in …
Covidx-net: A framework of deep learning classifiers to diagnose covid-19 in x-ray images
Background and Purpose: Coronaviruses (CoV) are perilous viruses that may cause Severe
Acute Respiratory Syndrome (SARS-CoV), Middle East Respiratory Syndrome (MERS-CoV) …
Acute Respiratory Syndrome (SARS-CoV), Middle East Respiratory Syndrome (MERS-CoV) …
Brain tumor classification using deep CNN features via transfer learning
Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for
medical applications. This paper focuses on a 3-class classification problem to differentiate …
medical applications. This paper focuses on a 3-class classification problem to differentiate …
[HTML][HTML] Artificial intelligence in pancreatic cancer
B Huang, H Huang, S Zhang, D Zhang, Q Shi, J Liu… - Theranostics, 2022 - ncbi.nlm.nih.gov
Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%.
The pancreatic cancer patients diagnosed with early screening have a median overall …
The pancreatic cancer patients diagnosed with early screening have a median overall …
Deep convolutional neural networks with transfer learning for automated brain image classification
MR brain image categorization has been an active research domain from the last decade.
Several techniques have been devised in the past for MR image categorization, starting from …
Several techniques have been devised in the past for MR image categorization, starting from …
Vision transformers, ensemble model, and transfer learning leveraging explainable AI for brain tumor detection and classification
The abnormal growth of malignant or nonmalignant tissues in the brain causes long-term
damage to the brain. Magnetic resonance imaging (MRI) is one of the most common …
damage to the brain. Magnetic resonance imaging (MRI) is one of the most common …
Artificial intelligence assists precision medicine in cancer treatment
Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the
same drugs or surgical methods in patients with the same tumor may have different curative …
same drugs or surgical methods in patients with the same tumor may have different curative …
Automated detection of COVID-19 cases from chest X-ray images using deep neural network and XGBoost
Introduction In late 2019 and after the COVID-19 pandemic in the world, many researchers
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
and scholars tried to provide methods for detecting COVID-19 cases. Accordingly, this study …
Cascaded deep learning classifiers for computer-aided diagnosis of COVID-19 and pneumonia diseases in X-ray scans
Computer-aided diagnosis (CAD) systems are considered a powerful tool for physicians to
support identification of the novel Coronavirus Disease 2019 (COVID-19) using medical …
support identification of the novel Coronavirus Disease 2019 (COVID-19) using medical …