In addition to pure deep neural networks (DNNs), sometimes people use hybrid vision models, which combine deep learning with classical machine learning algorithms that perform specific sub-tasks.

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 ...

With deep learning algorithms, standard CT technology produces spectral images. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2020 / 10 / 201019133700.htm ...

Self-teaching deep learning algorithm can find similar cases in large pathology image ... Chen, C., et al. (2022) Fast and scalable search of whole-slide images via self-supervised deep learning.

We wanted to focus on the eye, but each video frame mostly contained the externals of the infants’ face, the room etc. Our algorithm first removed all extraneous information,” explains Desai, who ...

Deep learning enables rapid detection of stroke-causing blockages. Assistance from the deep-learning algorithm improved the radiologists’ performance in detecting the cerebral aneurysms, increasing ...

Using a database of close to 130,000 images of skin diseases, the team was able to create an artificial intelligence algorithm able diagnose skin lesions with a performance level matching trained ...

For example, algorithms based on deep learning can determine the location and size of tumors. This is the result of AutoPET, an international competition in medical image analysis.