Breast cancer classification based on hybrid CNN with LSTM model
Jeddah University · Suez University
Abstract
Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. The speed-up process of detection and classification is crucial for effective cancer treatment. Medical image analysis methods and computer-aided diagnosis can enhance this process, providing training and assistance to less experienced clinicians. Deep Learning (DL) models play a great role in accurately detecting and classifying cancer in the huge dataset, especially when dealing with large medical images. This paper presents a novel hybrid model of DL models combined a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) for binary breast cancer classification on two datasets available at the…
Citation impact
- FWCI
- 125.32
- Percentile
- 100%
- References
- 45
Authors
4Topics & keywords
- Computer science
- Artificial intelligence
- Breast cancer
- Cancer
- Pattern recognition (psychology)
- Medicine
- Internal medicine