Marilisa Cortesi, Dongli Liu, Elyse Powell, Ellen Barlow, Kristina Warton, Caroline E. Ford
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引用次数: 0
摘要
准确识别癌细胞区分共培养物中不同类型细胞的贡献是一项重大挑战。Marilisa Cortesi、Caroline E. Ford 及其合作者通过一种基于深度学习的软件工具解决了这一难题。这种方法为在共培养中使用多种细胞类型（包括源自患者的细胞）提供了可能性。更多详情，请参阅文章编号 2400034。图片由 Tim Salita 博士创建。
Accurate Identification of Cancer Cells in Complex Pre-Clinical Models Using a Deep-Learning Neural Network: A Transfection-Free Approach (Adv. Biology 11/2024)
Accurate Identification of Cancer Cells
Distinguishing the contribution of different cell types in co-cultures is a major challenge. Marilisa Cortesi, Caroline E. Ford, and co-workers have addressed it through a deep learning-based software tool that distinguishes healthy and cancer cells solely from the shape of the nucleus. This method opens to the possibility of using a wide variety of cell types, including patient-derived ones, in co-cultures. More details can be found in article number 2400034. Image created by Dr. Tim Salita.
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