Inteligencia Artificial: marco de competencias para orientar prácticas supervisadas y aplicaciones de redes neuronales en estudiantes de Computación
Fecha
2025
Autores
Villalobos-Murillo, Johnny
Garita-González, Gabriela
Alfaro-Ramírez, Byron Jesús
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Universidad Peruana Cayetano Heredia (Perú)
Resumen
Resumen. La investigación exploratoria se centra en el desarrollo de competencias en Inteligencia Artificial y redes neuronales, Se llevó a cabo en el Laboratorio de Procesamiento de Imágenes, durante el I ciclo del 2023, con la participación de académicos y estudiantes que cursan la Práctica Profesional. Propone un marco de competencias y una metodología para clasificar mamografías en benignas y malignas, se desarrolla un modelo de aprendizaje automático. Utiliza un conjunto de datos con 118 imágenes de mamografías, previamente diagnosticas. Los resultados abarcan: la clasificación, los procesos de aprendizaje basado en competencias, resultados de aprendizaje y la rúbrica para la evaluación. Se crea una aplicación informática que integra la red neuronal. En conclusión, se evidencian avances significativos en el desarrollo de competencias en Inteligencia Artificial y redes neuronales, así como en la aplicación práctica en el campo de la salud en la clasificación de mamografías.
Abstract. The exploratory research focuses on the development of skills in Artificial Intelligence and neural networks. It was carried out in the Image Processing Laboratory during the first cycle of 2023, with the participation of academics and students enrolled in the Professional Practice course. It proposes a framework of skills and a methodology for classifying mammograms as benign or malignant, and a machine learning model is developed. It uses a dataset with 118 previously diagnosed mammogram images. The results cover: classification, competency-based learning processes, learning outcomes, and the rubric for evaluation. A computer application that integrates the neural network is created. In conclusion, significant advances are evident in the development of competencies in Artificial Intelligence and neural networks, as well as in the practical application in the field of health in the classification of mammograms.
Abstract. The exploratory research focuses on the development of skills in Artificial Intelligence and neural networks. It was carried out in the Image Processing Laboratory during the first cycle of 2023, with the participation of academics and students enrolled in the Professional Practice course. It proposes a framework of skills and a methodology for classifying mammograms as benign or malignant, and a machine learning model is developed. It uses a dataset with 118 previously diagnosed mammogram images. The results cover: classification, competency-based learning processes, learning outcomes, and the rubric for evaluation. A computer application that integrates the neural network is created. In conclusion, significant advances are evident in the development of competencies in Artificial Intelligence and neural networks, as well as in the practical application in the field of health in the classification of mammograms.
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Palabras clave
INTELIGENCIA ARTIFICIAL, APRENDIZAJE, REDES NEURONALES (INFORMATICA), ARTIFICIAL INTELLIGENCE, LEARNING, NEURAL NETWORKS (COMPUTER SCIENCE)
