Frontiers

Automated predictive framework using AI and deep learning approaches for early detection and classification of liver cancer

Liver cancer, including hepatocellular carcinoma (HCC), is a leading cause of cancer-related deaths globally, emphasizing the need for accurate and early detection methods. LiverCompactNet classifies ...
IEEE

Assessment of 3D MRI Image segmentation and Classification for Brain Tumor Detection Using ConvLSTM

Abstract: The human brain serves as the principal controller of the humanoid system. Brain tumors are the result of abnormal cell division and proliferation, and the development of these tumors can ...
C&EN

NPClassifier: A Deep Neural Network-Based Structural Classification Tool for Natural Products

Center for Marine Biotechnology and Biomedicine, Scripps Institution of Oceanography, University of California San Diego, La Jolla, California 92093, United States ...
Scientific Research Publishing

Leveraging Pima Dataset to Diabetes Prediction: Case Study of Deep Neural Network ()

Laboratory of Data Science and Digital Inclusion, Institut de Mathématiques et de Sciences Physiques, Université d’Abomey-Calavi, Abomey-Calavi, Bénin. Diabetes is a chronic disease. In 2019, it was ...
acm.org

Deep Learning for AI

Yoshua Bengio, Yann LeCun, and Geoffrey Hinton are recipients of the 2018 ACM A.M. Turing Award for breakthroughs that have made deep neural networks a critical component of computing. Research on ...
GitHub

Model Zoo

Check out the model zoo documentation for details. 16-layer: 7.5% top-5 error on ILSVRC-2012-val, 7.4% top-5 error on ILSVRC-2012-test 19-layer: 7.5% top-5 error on ...
PNAS

Improving the taxonomy of fossil pollen using convolutional neural networks and superresolution microscopy

We demonstrate that combining optical superresolution imaging with deep learning classification methods increases the speed and accuracy of assessing the biological affinities of fossil pollen taxa.