Whether you need to perform simple tasks or complex analysis of multiplex markers, artificial intelligence can improve performance and facilitate your analysis tasks to unlock the information hidden in image data.
TORONTO (PRWEB) March 19, 2021
Which artificial intelligence method will work best with your image data?
Image analysis is an essential part of digital pathology, from research and discovery of targets and biomarkers to understanding the tumor microenvironment to development of novel therapeutics. Whether you need to perform simple tasks or complex analysis of multiplex markers, artificial intelligence can improve performance and facilitate your analysis tasks to unlock the information hidden in image data.
During the last years, deep learning algorithms have revolutionized the quality of analysis and allowed accurate assessment of highly heterogeneous and previously challenging tissue structures. In order to best utilize the capabilities that AI methods offer, however, it is important to understand what the terms “artificial intelligence” (AI), “machine learning” (ML), and “deep learning” (DL) really refer to when it comes to image analysis.
This webinar will define the important differences between each term, provide an understanding of their roles in image analysis, and help you to decide when to employ each method in your research.
For more information, or to register for this event, visit Artificial Intelligence in Digital Pathology.
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