How far have we come? Artificial intelligence for chest radiograph interpretation
Due to recent advances in artificial intelligence, there is renewed interest in automating
interpretation of imaging tests. Chest radiographs are particularly interesting due to many …
interpretation of imaging tests. Chest radiographs are particularly interesting due to many …
A review on prediction and prognosis of the prostate cancer and gleason grading of prostatic carcinoma using deep transfer learning based approaches
GP Kanna, SJKJ Kumar, P Parthasarathi… - … Methods in Engineering, 2023 - Springer
Prostate cancer is a dangerous type of cancer that kills a lot of men because it is hard to
diagnose. Images taken of people with carcinoma have complex and important parts that are …
diagnose. Images taken of people with carcinoma have complex and important parts that are …
Deep cascade learning
ES Marquez, JS Hare… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
In this paper, we propose a novel approach for efficient training of deep neural networks in a
bottom-up fashion using a layered structure. Our algorithm, which we refer to as deep …
bottom-up fashion using a layered structure. Our algorithm, which we refer to as deep …
Urinary stone detection on CT images using deep convolutional neural networks: evaluation of model performance and generalization
Purpose To investigate the diagnostic accuracy of cascading convolutional neural network
(CNN) for urinary stone detection on unenhanced CT images and to evaluate the …
(CNN) for urinary stone detection on unenhanced CT images and to evaluate the …
Quantum transfer learning for breast cancer detection
V Azevedo, C Silva, I Dutra - Quantum Machine Intelligence, 2022 - Springer
One of the areas with the potential to be explored in quantum computing (QC) is machine
learning (ML), giving rise to quantum machine learning (QML). In an era when there is so …
learning (ML), giving rise to quantum machine learning (QML). In an era when there is so …
[HTML][HTML] Checklist for responsible deep learning modeling of medical images based on COVID-19 detection studies
W Hryniewska, P Bombiński, P Szatkowski… - Pattern Recognition, 2021 - Elsevier
The sudden outbreak and uncontrolled spread of COVID-19 disease is one of the most
important global problems today. In a short period of time, it has led to the development of …
important global problems today. In a short period of time, it has led to the development of …
Sequential modeling of deep features for breast cancer histopathological image classification
Computerized approaches for automated classification of histopathology images can help in
reducing the manual observational workload of pathologists. In recent years, like in other …
reducing the manual observational workload of pathologists. In recent years, like in other …
Fine-tuning pre-trained convolutional neural networks for gastric precancerous disease classification on magnification narrow-band imaging images
Gastric cancer (GC) is the fourth leading cause of cancer death worldwide. To prevent the
occurrence of advanced GCs, there is a need for immediate detection and treatment of …
occurrence of advanced GCs, there is a need for immediate detection and treatment of …
Deep learning based image classification for intestinal hemorrhage
Convolutional neural networks (CNN) have become a popular choice for image
segmentation and classification. Internal body images are obscure in nature with …
segmentation and classification. Internal body images are obscure in nature with …
Quantum machine learning in prediction of breast cancer
Abstract Machine learning (ML) is the most promising subset of artificial intelligence.
Quantum computing is prevalent for fast problem-solving approaches. The complex …
Quantum computing is prevalent for fast problem-solving approaches. The complex …