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Immunotherapy is a treatment that boosts or manipulates the immune system to fight diseases, including cancer. For instance, by stimulating an immune response through vaccinations against viruses that cause cancers, like hepatitis B virus and human papillomavirus, these diseases can be prevented. Nonetheless, some cancer cells can avoid the immune system due to their rapid mutation and division. The immune response to many cancers involves three phases: elimination, equilibrium, and escape.
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Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
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The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Sistema de Inteligencia Artificial Multiagente Inspirado en Tumor Board para Interpretar Guías Oncológicas

Jiasheng Wang1, Kirti Arora2, David M Swoboda3

  • 1Division of Hematology, Department of Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH.

JCO clinical cancer informatics
|January 7, 2026
PubMed
Resumen

Un nuevo sistema de inteligencia artificial (IA) multiagente recupera e interpreta con precisión las guías clínicas oncológicas, superando significativamente las herramientas de IA existentes para responder preguntas complejas sobre la atención al paciente.

Palabras clave:
inteligencia artificialguías oncológicasatención oncológicasoporte de decisión clínicamedicina de precisión

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