In 2020, there were more than 1.2 million new skin cancer diagnoses, and melanoma was the most recurrent type of cancer. On the other hand, melanoma is the least common but most serious form of skin cancer affecting both men and women. This work aims to assemble classification models to detect a case of melanoma with high accuracy based on a Convolutional Neural Networks system. The methodology considers training 21 models for image classification, with the best assembly performance of EfficientNet and VGG-19 architectures, the data augmentation technique was used to the images to improve its performance. The results show 92.85% of accuracy, 71.50% of sensitivity, and 94.89% of specificity, with an improvement of 0.06% in accuracy and specificity. The assembly of the classification models achieved higher accuracy in melanoma skin cancer image classification.
La preferencia de las personas por acceder a contenidos publicitarios por medio de aplicaciones digitales es cada vez mayor mientras que muchos negocios un siguen utilizando los medios tradicionales, lograr una comunicación con el cliente sin caer en mensajes spam o invasivos es un reto mayor para las empresas.Por tales motivos proponemos una aplicación móvil que obtenga las preferencias de las personas y les comunique información publicitaria relevante en el lugar y momento precisos. Para el desarrollo de la aplicación se utiliza la metodología en cascada puesto que sigue siendo el enfoque más utilizado en el desarrollo de software. Para seleccionar la tecnología que más se adapta a la necesidad del proyecto se obtuvo un mayor puntaje con la tecnología Beacon Bluetooth en comparación con otras tecnologías de proximidad en un análisis de Benchmarking. Nuestro resultado es una exitosa comunicación con los clientes al presentarle información publicitaria relevante en el momento y lugar preciso sin ser invasivo, así mismo podíamos proporcionar a las empresas la información del seguimiento de los clientes para poderles brindar mayores beneficios; de esa manera cumplimos con los objetivos propuestos. PALABRAS CLAVEMarketing de proximidad, Beacon, Bluetooth, Aplicaciones móviles, Publicidad.3C TIC. Cuadernos de desarrollo aplicados a las TIC.
This paper proposes a technology adoption model called TAM 4, based on the TAM model considering the trust and perceived risk factors to the adoption of technology in response to governments' concern to achieve competitiveness in the most important economic activities. The methodology used considers the predictive method. The sample was selected from 67 companies related to foreign trade that carry out agro export tasks, with a confidence level of 90% and an error percentage of ± 10% and the 0.787 of Cronbach's Alpha obtained for the instrument's validation. In conclusion, 97% of the companies informally adopt technology. This shows that 68% of the companies surveyed in the sector would be willing to adopt the model.
The objective of this research is to reduce the dropout rate of students in the Faculty of Systems Engineering and Informatics of the Universidad Nacional Mayor de San Marcos – FISI-UNMSM, through the implementation of an intelligent system with a data mining approach and the autonomous learning algorithm (decision trees) that predicts which students are at risk of dropping out. It was developed in Python and the free software Weka, for this purpose student data was collected from 2014 to 2020. This solution increases the availability and the level of satisfaction of the faculty; in the learning process, an accuracy percentage of 90.34% and precision of 95.91% was obtained, so the data mining model is considered valid. In addition, it was found that the variables that most influenced students in making the decision to abandon their studies were the historical weighted average, the weighted average of the last cycle and the number of credits passed.
SISTEMA EXPERTO PARA LA PREVENCIÓN DE ENFERMEDADES BASADO EN EL CONSUMO DE ALIMENTOS COTIDIANOS EXPERT SYSTEM FOR ILLNESSES PREVENTION BASED ON THE DAILY FOOD CONSUMPTION Hugo Vega H., Augusto Cortez V. y Ana M. Huayna D. Universidad Nacional Mayor de San Marcos, Av. Germán Amezaga s/n Lima 1, Lima, Perú DOI: https://doi.org/10.33017/RevECIPeru2010.0007/ RESUMEN A lo largo de la existencia humana, el tratamiento de las enfermedades siempre ha sido una preocupación constante. Ahora que la población mundial se ha incrementado y las enfermedades se han multiplicado, la venta de medicamentos se ha convertido en uno de los principales negocios en el mundo. Así mismo como se sabe, la medicina naturista es una alternativa muy importante en el tratamiento y prevención de las enfermedades. Teniendo en cuenta estas premisas, hemos realizado una importante investigación la misma que nos ha permitido generar el presente artículo. El objetivo del presente artículo es explicar el modelamiento de un Sistema Experto para la Prevención y Tratamiento de Enfermedades basado en el consumo de potajes o dietas diarias En resumen, el Sistema Experto (SE) que hemos modelado permite registrar como entrada síntomas, enfermedades o resultados de exámenes médicos de un paciente y genera como salida un listado de alternativas de platos o potajes que el paciente debe consumir, en su desayuno, almuerzo y cena. De ese modo, el paciente aliviará sus males, manteniendo en lo posible sus normales hábitos de consumo de alimentos. Por cierto el SE será el encargado de establecer el vínculo de los platos o potajes recomendados por el sistema con los productos naturales que alivian los síntomas registrados como entrada. Obviamente, para cada paciente con síntomas diferentes, es de esperar que el SE le recomiende diferentes potajes. Palabras clave: Sistema Experto, Base de Conocimiento, Prevención de Enfermedades, Medicina Natural. ABSTRACT Throughout human existence, the treatment of illnesses has always been a constant concern. Now that the world population has increased and the illnesses have multiplied, the sale of drugs has become one of the main businesses in the world. Like we know, natural medicine is an important alternative in the treatment and prevention of illnesses. Given these assumptions, we have made an important investigation it has allowed us to generate this article. The objective of this article is to explain the how to model an Expert System for the prevention and treatment of illnesses based on the daily food consumption. In summary, the Expert System (ES) that we have modelling, permit you to register as entry symptoms, illnesses, or medical test results from a patient and generates as output a list of alternatives of foods that the patient should consume at breakfast, lunch, and supper. Thus, the patient relieves their symptoms, maintaining where possible their normal food consumption habits. Of course the ES will be responsible for the linkage of the dishes recommended by the system with natural products that relieve the symptoms registered as input. Obviously, for each patient with different symptoms, it is hoped that ES recommend different dishes. Keywords: Sistema Experto, Base de Conocimiento, Prevención de Enfermedades, Medicina Natural.
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