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Main Topic: AI-enabled model (Lymphovision) for lymphoma diagnosis and prognosis.
Key Findings (as presented at ASH Annual Meeting and Exposition):
* Differentiation: Lymphovision reliably differentiates between lymphoma and reactive tissue.
* Subtyping: it can identify genetic subtypes of lymphoma.
* Relapse Prediction: It can assess the likelihood of relapse.
* Data Source: All of this is achieved using routine histology.
Expert Quote:
* Stephen M. Ansell, MD, PhD: “I think we’re at a very exciting time, with lots of things going on, all of which make for a good outcome in general for patients with lymphoma.” (professor of Medicine, Chair of Hematology, Co-leader of Hematological Malignancies programme, Interim chair of Oncology at Mayo Clinic)
Source Information:
* Source: Healio Interviews
* Reference: Seheult J, et al. Abstract 117. Presented at: ASH Annual Meeting and Exposition; Dec. 6-9, 2025; Orlando.
* Disclosures: Stephen M. Ansell reports no relevant financial disclosures.
Publisher:
* hemonc today (Healio)
Additional Information:
* There’s a promotion for “Healio AI” – a tool that allows users to ask clinical questions and access a knowledge base including PubMed, trials, guidelines, and Healio’s news coverage.
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