Here, we look at the growing applications of AI-driven spatial imaging techniques in healthcare, focusing on interpreting the 3D genome through cell imaging. AI can assist in understanding intricate data patterns, enabling an improved understanding of cell behaviour and diseases.
Advances in spatial imaging have revolutionised disease analysis, revealing new therapeutic targets and biomarkers. However, efficiently interpreting the vast amount of data generated remains a challenge.
CRISPR-based animal models expedite drug development by enhancing accuracy, replicating human physiology, reducing time and cost, aiding in predicting treatment efficacy, and addressing safety concerns in clinical trials.
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