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Desarrollo y validación de un modelo interpretable de aprendizaje automático para discriminar entre cáncer de mama
Zhichun Wang1, Weixiang Liu2, Lin Hua3
1Department of Breast Surgery, Jiujiang City Key Laboratory of Cell Therapy/Human Genetic Resources Innovation Center, The First People's Hospital of Jiujiang City, Jiujiang, China.
Un nuevo modelo logístico que utiliza datos clínicos y de laboratorio de rutina distingue eficazmente las lesiones mamarias malignas de las benignas. Esta herramienta ayuda a la estratificación temprana del riesgo, reduciendo potencialmente las biopsias innecesarias para la detección del cáncer de mama.
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