这篇文章介绍了一个名为 PhenoProfiler 的创新模型，它旨在高效且有效地从图像中提取细胞的形态表征，以推进基于图像的药物发现。不同于现有需要复杂多步骤流程的方法，PhenoProfiler 作为一个端到端的工具，可以直接处理多通道全玻片图像，并利用多目标学习模块来增强鲁棒性和泛化能力。该模型在超过 230,000 张图像的大型公共数据集上进行了严格评估，结果显示其在生物匹配任务中性能显著优于现有技术，最高提升达 20%。此外，PhenoProfiler 还引入了一种表型校正策略来强调治疗引起的相对变化，从而提高了生物信号的检测能力，并提供了一个用户友好的 Python 包和网页服务器。References: Li, Bo, et al. "PhenoProfiler: Advancing Phenotypic Learning for Image-based Drug Discovery." arXiv preprint arXiv:2502.19568 (2025).
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