Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right). Credit: Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00912-9 ...

U of T researchers have developed a deep learning algorithm that can track proteins to help reveal what makes cells healthy and what goes wrong in disease. From self-driving cars to computers that can ...

All deep learning models are built on fundamental computational units that take in inputs, process them, and produce outputs—either forwarding them to the next layer or using them as the final ...

Precision medicine is a fast-growing field whereby medical treatments are tailored to individual patients – taking factors like genetics and lifestyle into account. A key part of this process is ...

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome The methods help identify 'footprints' that indicate binding sites and reveal ...

Clinical Photographic Images: Deep learning algorithms such as DenseNet-169, ResNet-101, and EfficientNet-b4 have been employed to analyze clinical photographs of oral lesions.

Clinical Photographic Images: Deep learning algorithms such as DenseNet-169, ResNet-101, and EfficientNet-b4 have been employed to analyze clinical photographs of oral lesions.

MARBLE: interpretable representations of neural population dynamics using geometric deep learning. Nature Methods, 2025; DOI: 10.1038/s41592-024-02582-2 ...