Automatic extraction of lightweight and efficient neural network architecture of heavy convolutional architectures to predict microsatellite instability from hematoxylin and eosin histology in gastric cancer.

MLA

Rostami, Habib, et al. “Automatic Extraction of Lightweight and Efficient Neural Network Architecture of Heavy Convolutional Architectures to Predict Microsatellite Instability from Hematoxylin and Eosin Histology in Gastric Cancer.” Neural Computing & Applications, vol. 36, no. 25, Sept. 2024, pp. 15295–321. EBSCOhost, https://doi.org/10.1007/s00521-024-09882-w.

APA

Rostami, H., Ashkpour, M., Behzadi-Khormouji, H., Mokhtari, M., Khayati, A., Keshavarz, A., Talatian Azad, S., & Tabesh, Y. (2024). Automatic extraction of lightweight and efficient neural network architecture of heavy convolutional architectures to predict microsatellite instability from hematoxylin and eosin histology in gastric cancer. Neural Computing & Applications, 36(25), 15295–15321. https://doi.org/10.1007/s00521-024-09882-w

Chicago

Rostami, Habib, Maryam Ashkpour, Hamed Behzadi-Khormouji, Maral Mokhtari, Armin Khayati, Ahmad Keshavarz, Saeed Talatian Azad, and Yahya Tabesh. 2024. “Automatic Extraction of Lightweight and Efficient Neural Network Architecture of Heavy Convolutional Architectures to Predict Microsatellite Instability from Hematoxylin and Eosin Histology in Gastric Cancer.” Neural Computing & Applications 36 (25): 15295–321. doi:10.1007/s00521-024-09882-w.