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Found 4 papers, 2 papers with code
Towards Explainable End-to-End Prostate Cancer Relapse Prediction from H&E Images Combining Self-Attention Multiple Instance Learning with a Recurrent Neural Network
On the use case of prostate cancer survival prediction, using 14, 479 images and only relapse times as annotations, we reach a cumulative dynamic AUC of 0. 78 on a validation set, being on par with an expert pathologist (and an AUC of 0. 77 on a separate test set).
Deep learning-based bias transfer for overcoming laboratory differences of microscopic images
The automated analysis of medical images is currently limited by technical and biological noise and bias.
Combining Multiple Views for Visual Speech Recognition
In this paper, we explore this aspect and provide a comprehensive study on combining multiple views for visual speech recognition.
Visual Speech Recognition Using PCA Networks and LSTMs in a Tandem GMM-HMM System
Automatic visual speech recognition is an interesting problem in pattern recognition especially when audio data is noisy or not readily available.
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