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 ...

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 ...

Deep learning (DL) methods offer a promising solution by reconstructing raw, low-quality data into high-resolution images, helping to preserve diagnostic accuracy even under time constraints.

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 ...

Medical apps will become a reality and wearables will replace many visits to the doctor’s office. Computer vision (CV) through machine learning can perform image classification, segmentation ...

He has developed algorithms for medical image filtering, segmentation and search. He is the author of two books, 14 book chapters, and more than 140 journal and conference papers.

Furthermore, deep learning algorithms trained with optical coherence tomography (OCT) data can detect microstructural damage due to glaucoma and its progression over time.

At last week’s APS March Meeting, a dedicated focus session examined some of the latest medical applications of artificial intelligence and machine learning. In-depth image analysis Opening the ...

Upon analysis, the researchers found no significant difference in performance between the segmentations made between a human and AI algorithm team, compared to those made only by human medical ...