AIVIS (CEO Daehong Lee), a company specializing in artificial intelligence (AI)-powered pathology image analysis solutions, announced today that it presented its research findings on the performance validation of its breast cancer Ki-67 Digital Image Analysis (DIA) at ESMO Breast Cancer 2026, held in Berlin, Germany, from May 6 to 8. ESMO Breast Cancer 2026 is a premier academic conference where global breast cancer researchers and clinical experts convene to share the latest research milestones and innovative treatment strategies. The event was held on-site in Berlin, alongside virtual sessions for global accessibility. Ki-67 is a critical biomarker used to evaluate tumor cell proliferation in breast cancer, playing a key role in determining therapeutic pathways and assessing patient prognosis. However, traditional visual assessment by pathologists can lead to significant inter-observer variability. Consequently, there is an accelerating industry demand for improved reproducibility and objective quantification through digital pathology-based AI analysis. In this study, AIVIS presented a standardized validation framework capable of objectively evaluating Ki-67 DIA performance by utilizing the test dataset from "BCData," a publicly available breast cancer Ki-67 dataset. The dataset comprises 402 image patches of 640×640 pixels captured at 400x magnification, featuring expert annotations for a total of 21,864 Ki-67 positive tumor cells and 43,568 negative tumor cells. AIVIS's proprietary Qanti® Breast Ki-67 AI model was deployed for the validation study. The analysis demonstrated a remarkably strong correlation between the predictions generated by the Qanti® Breast Ki-67 AI model and the expert ground-truth annotations. The number of positive and negative tumor cells predicted by the AI yielded exceptionally high Spearman correlation coefficients of 0.966 and 0.871, respectively, compared to the actual annotated values. Furthermore, the overall Ki-67 proliferation index displayed a powerful correlation with a Spearman correlation coefficient of 0.957. Statistical significance was firmly established across all major correlation analyses ($p < 0.001$). Additionally, a discordance analysis evaluating clinically meaningful classification variations based on a standard 20% cut-off threshold revealed a remarkably low discordance rate of just 5.47%. The significance of this study extends beyond merely showcasing high-performance metrics for an AI model; it establishes a practical, standardized evaluation approach to validate Ki-67 DIA solutions using public datasets. As the clinical sector increasingly demands objective benchmarks to verify DIA tools, this public dataset-based validation framework is expected to enhance the credibility of digital pathology AI solutions and accelerate their real-world clinical adoption. Daehong Lee, CEO of AIVIS, stated: "Our presentation at ESMO Breast Cancer 2026 is highly meaningful as it allows us to showcase AIVIS's AI-driven quantitative biomarker analysis technology and validation methodologies on an international academic stage. AIVIS will continue to expand the capabilities of pathology AI across a diverse spectrum of oncology beyond breast cancer. Moving forward, we aim to deliver tangible value in precision medicine and targeted drug discovery—moving far beyond simple diagnostic assistance—by consistently scaling up our global research collaborations and commercial pipelines." AIVIS has been successfully translating its AI-based pathology image analysis research into real-world clinical settings and high-value global partnerships. Centered around its flagship product "Qanti IHC"—which has received regulatory approval from the South Korean Ministry of Food and Drug Safety (MFDS)—the company has accumulated extensive clinical deployment experience through digital pathology integration and Proof of Concept (PoC) initiatives at over 20 major medical institutions. Concurrently, AIVIS is refining its R&D quantitative biomarker analysis capabilities via its dedicated discovery platform, "Qanti Discovery." The company continues to drive collaborative research with global medical device and pharmaceutical leaders in Companion Diagnostics (CDx), drug discovery, and biomarker analysis. Notably, AIVIS has recently expanded its pathology AI footprint across the entire lifecycle of precision medicine and drug development, highlighted by a joint research agreement with Antibody-Drug Conjugate (ADC) specialist AimedBio and securing a strategic investment (SI) from them.