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A blood-based classifier for differential diagnosis of feline IBD and enteropathy-associated T-cell lymphoma

Veterinary Cancer Society Annual Conference 2026
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From Prediction to Practice: Clinical Outcomes, Treatment Economics, and the Evolving Role of AI in Canine Lymphoma Care

Veterinary Cancer Society Annual Conference 2026
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Retrospective cost analysis of machine learning–guided chemotherapy selection in dogs with relapsed B-cell lymphoma, stratified by prediction-treatment concordance

Veterinary Cancer Society Annual Conference 2026
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Drug Response Prediction–Guided Treatment Selection Is Associated with Improved Survival and Remission in Canine T-Cell Lymphoma

Veterinary Cancer Society Annual Conference 2026
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How ImpriMed Turned Nine Years in Veterinary Oncology Into a Human Blood Cancer Business

SynBioBeta
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ImpriMed CEO Dr. Sungwon Lim Invited to National Cancer Institute Panel on Commercializing Functional Precision Medicine

BusinessWire
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Flow Cytometry's Prognostic Insights in Canine Lymphoma

ACVIM Forum 2026
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Harnessing AI, Immunophenotyping, and Drug Sensitivity Testing for Individualized Canine Lymphoma Treatment

ACVIM Forum 2026
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A Multi-Modal Tool for Differential Diagnosis of Feline IBD and EATL Using Minimally Invasive Specimens

ACVIM Forum 2026
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Integrating genomic and ex vivo drug sensitivity profiling to predict treatment outcomes in Korean patients with non-Hodgkin lymphoma

Biotechnology and Bioprocess Engineering
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A multi-omic approach to biomarker discovery for the differential diagnosis of feline IBD and EATL using minimally invasive specimens

Veterinary Cancer Society Collaborative Conference 2025
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Quantitative ex vivo synergy profiling uncovers heterogeneous combination responses in acute myeloid leukemia

Biotechnology and Bioprocess Engineering
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Quantitative ex vivo assessment of chemotherapy synergy using patient-derived non-Hodgkin lymphoma samples

Biotechnology and Bioprocess Engineering
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Health Tech: Valerie Goodwin-Adams of ImpriMed On How Their Technological Innovations Will Shake Up The Tech Scene

Authority Magazine
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Quantitative ex vivo synergy profiling uncovers heterogeneous combination responses in AML primary samples

67th ASH Annual Meeting and Exposition
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Ex vivo drug sensitivity testing in Korean AML patients: Integration of functional and genomic profiles for predicting clinical response and survival

67th ASH Annual Meeting and Exposition
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A multi-institutional machine-learning score that predicts bacteremia and gram class at blood-culture initiation

67th ASH Annual Meeting and Exposition
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ImpriMed to Present Ex Vivo Drug Sensitivity Data in Acute Myeloid Leukemia in Oral Presentation at American Society of Hematology Annual Meeting

PR Newswire
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