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Aprendizaje de la Similitud del Paciente a partir de Genómica para Oncología de Precisión
Maha Shady1,2,3,4, Brendan Reardon3,4, Sharon Jiang2,3,4
1Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
medRxiv : the preprint server for health sciences
|December 25, 2025
Resumen
Un nuevo modelo de aprendizaje profundo identifica la similitud del paciente utilizando datos genómicos tumorales. Este enfoque ayuda en las decisiones de tratamiento, especialmente para pacientes que carecen de biomarcadores o con cánceres raros.
Sus antecedentes:
- La oncología de precisión se basa en biomarcadores moleculares, pero muchos pacientes carecen de dianas accionables o tratamientos efectivos.
- Los enfoques de similitud del paciente pueden mejorar el soporte de decisiones al analizar perfiles tumorales completos y datos clínicos de grandes cohortes de pacientes.
Conclusiones:
- El marco basado en la similitud traduce datos complejos en información procesable para la oncología de precisión.
- Este enfoque aumenta el juicio clínico y apoya la toma de decisiones centrada en el paciente.
- Proporciona una base para un modelo de soporte de decisiones de aprendizaje en tiempo real en oncología de precisión.
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