Use the AI Kit for Spatial Single-Cell Analysis
Learn about implementing the Intel® AI Analytics Toolkit (AI Kit) in medical imaging. Explore single-cell data (like an RNA sequence) through imaging and gene expression profiling.
The speakers ported Squidpy to the AI Kit. Squidpy produces highly interactive visualizations that enable intuitive exploration of single-cell spatial molecular data. This process has several optional uses (like analyzing neighborhood graphs and computing spatial statistics) to facilitate the exploration of tissue images.
From huge datasets, create spatial graphs and do image analysis. Extract the image and summary features. From the image features, generate a cluster annotation that helps you study spots. Compute neighborhood enrichment that can help identify spot (node) clusters that share a common neighborhood structure across the tissue. Uncover molecular mechanisms associated with cell differentiation and disease progression.
Use the results for:
- Finding abnormalities in gene expression
- Disease progression
Abhishek Nandy is cofounder of Dynopii. He has a bachelor of technology degree and a curious mind. He is also an Intel® Black Belt Software Developer, a coveted open source award given to people who have contributed to Intel's open source projects. He has presented his research work on reinforcement learning at the Association for Computing Machinery (ACM) SIGGRAPH 2018. Abhishek is an invited educator at several leading premier education institutes in India.
Abhishek has also authored books on reinforcement learning, Unity* machine learning, Leap Motion*, and game engines. He was also among the top 50 innovators at the first edition of the Make in India initiative.
Product and Performance Information
Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.