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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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Predicting Chemotherapy Response in Patients With Advanced or Metastatic Pancreatic Cancer Using Machine Learning

JCO Clinical Cancer Informatics
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ImpriMed Accelerates Growth With Strategic Leadership Hire and Major Operational Milestones

Business Wire
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Large-Scale Validation of a Flow Cytometry Platform for Comprehensive Immunophenotyping, Cell Size Determination, and Prognostic Stratification in Canine Lymphomas

Veterinary Cancer Society Annual Conference 2025
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Lumps, Lab Work, and a Little AI: A Tech’s Guide to Canine Lymphoma

Veterinary Cancer Society Annual Conference 2025
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When AI Disappoints: Improving Outcomes with Real-World Clinical Data

Veterinary Cancer Society Annual Conference 2025
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Ethos Discovery Stratified Outcomes for Lymphoma in Dogs (SOLID) Study: Informing Subclassification & Prognosis

ACVIM Forum 2025
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Identification of novel genetic mutations for the treatment prognostication of canine lymphoma

npj Precision Oncology
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Chemotherapy selection for advanced or metastatic pancreatic cancer using machine learning models trained with multi-center datasets

2025 ASCO Gastrointestinal Cancers Symposium
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Optimizing the first line therapy of canine B-cell lymphomas via machine learning

Symposium on Artificial Intelligence in Veterinary Medicine (SAVY) 2.0
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How Artificial Intelligence Is Revolutionising Cancer Care for Pets

Pets Magazine
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AI, Cancer & the Future of Pet Care with Dr Ilona Holcomb

The Pets Mag Podcast
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