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Taming chaos in neural networks: A biologically plausible way

A new framework that causes artificial neural networks to mimic how real neural networks operate in the brain has been ...
ascopubs.org

Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality ...

Predicting Response of Triple-Negative Breast Cancer to Neoadjuvant Chemotherapy Using a Deep Convolutional Neural Network–Based Artificial Intelligence Tool The best performing model, a Bi-LSTM NER ...

Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
ascopubs.org

Novel Generative Recurrent Neural Network Framework to Produce Accurate, Applicable, and Deidentified Synthetic Medical Data for Patients With Metastatic Cancer

Risk Factors of Hyperglycemia After Treatment With the AKT Inhibitor Ipatasertib in the Prostate Cancer Setting: A Machine Learning–Based Investigation We analyzed a metastatic cancer patient cohort ...

A unified model of memory and perception: How Hebbian learning explains our recall of past events

A collaboration between SISSA's Physics and Neuroscience groups has taken a step forward in understanding how memories are ...
JSTOR Daily

Restoration of fragmentary Babylonian texts using recurrent neural networks

The main sources of information regarding ancient Mesopotamian history and culture are clay cuneiform tablets. Many of these tablets are damaged, leading to missing information. Currently, the missing ...