Dive into our latest white paper alongside IAMLAB, where we explore the transformative power of AI in pathology, its integration challenges, and the innovative solutions offered by PathcoreFlow's open API. Discover how AI, along with PathcoreFlow is reshaping the field and streamlining research processes for a brighter future in healthcare.

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Executive Summary

The incorporation of artificial intelligence (AI) into digital pathology research and development is a complex process. Pathologists often encounter challenges such as the subjective and timeintensive analysis of large image datasets. AI emerges as a transformative tool with significant potential to reduce both subjectivity and analysis time. However, applying AI to digital pathology is not without challenges. The nuances of AI integration in digital pathology are explored in this white paper, focusing on how the Image Analysis in Medicine Lab (IAMLAB) is leveraging PathcoreFlow, an open Information Management System with a robust Application Programming Interface (API), to perform research in this field.

PathcoreFlow simplifies data management by allowing seamless access to Whole Slide Images (WSIs), annotations, overlays, and metadata through the cloud, as well as streamlining the collection of annotations from multiple pathologists. It also facilitates the efficient patching of slides for AI studies using tools that leverage the API. An international study involving 90 pathologists conducted by IAMLAB demonstrates that an AI tool integrated into PathcoreFlow significantly improves accuracy, inter-rater agreement, and evaluation time when assessing the Ki-67 biomarker in breast cancer. This white paper illuminates the role of AI in digital pathology research and highlights its potential through PathcoreFlow.

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