The future of automated labeling in histology is promising, with ongoing advancements in AI and computational power. Improved algorithms are expected to handle more complex image analyses with greater accuracy. Additionally, integration with other technologies, such as digital pathology and 3D imaging, is likely to enhance its capabilities further. As these technologies evolve, automated labeling could become an indispensable tool in both research and clinical environments, ultimately improving patient outcomes and advancing scientific knowledge.
