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 ...

Deep-learning algorithms provide a way to automate the analysis of connectomics data while still achieving high accuracy. How to make spatial maps of gene activity — down to the cellular level ...

Please use one of the following formats to cite this article in your essay, paper or report: APA. Cuffari, Benedette. (2025, April 07). Using Deep Learning for Brain Imaging Data Analysis.

Deep Learning Pioneer Geoffrey Hinton Publishes New Deep Learning Algorithm This item in japanese Jan 10, 2023 2 min read ...

Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the ...

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.

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome. ScienceDaily . Retrieved July 12, 2025 from www.sciencedaily.com / releases ...

A deep reinforcement learning algorithm can solve the Rubik's Cube puzzle in a fraction of a second. The work is a step toward making AI systems that can think, reason, plan and make decisions.

Figuring out the ways in which algorithms and deep learning models are different is a good start if the goal is to reconcile them. Deep learning can’t generalize For starters, Blundell said ...