4 research outputs found
Convergent One‐Pot Synthesis of 3‐Substituted Quinazolin‐4(3H)‐ones under Solvent‐Free Conditions.
No full textThe Causal Relationship of Motivational Variables and Academic Performance in Science: Mediation by Conceptual Understanding in the girls and boys eighth-grade students
No full textBackground and Objective:In various studies, the factors affecting academic achievement and performance are divided into two categories: the first category are variables and factors that are outside the learner and include factors such as teacher teaching method and socio-economic status of students and the category; the second are the variables that are related to the learner and are known as personal factors that include motivation, attitude, self-efficacy and cognitive factors. From the perspective of educational psychologists as well as teachers, motivation is one of the key concepts and is used to explain different levels of student performance. The purpose of this study was to examine the causal relationship between motivational variables and academic performance in science, mediated by conceptual understanding in male and female students of the eighth grade. Methods: The sample was recruited from all of eighth grade students in Darab city, Iran. The research method was correlational. The data gathered through the three questionnaires: the modified version of Harter's (1980, 1981) scale, Attitude Survey Questionnaire, and the researcher-made conceptual understanding of Science. In the descriptive section, the mean, standard deviation and correlation coefficient were used and in the inferential section, structural equation modeling was used. Findings: The results showed that all relationships between variables, except the extrinsic motivation for conceptual understanding were significant. Results also indicated that all indirect hypotheses, except the indirect relation of extrinsic motivation to the academic performance in science mediated by conceptual understanding were confirmed. Conclusion: In the explanation of the present study that there is no significant relationship between external motivation and conceptual understanding, it can be pointed out that students who are motivated externally, study activities simply to achieve the desired outcomes such as approval or reward and prevent undesirable consequences such as punishment. In other words, the external factor controls their behavior and encourages them to perform a specific activity. According to behaviorists, learning is a change in the obvious behavior of the individual and its realization requires the use of positive and negative reinforcers. And these environmental stimuli, which are used to reinforce or inhibit observable behaviors, lead to behavioral changes. Since behaviorists focus on observable and measurable behaviors, not on inaccessible mental processes, and given that conceptual understanding is a mental process related to one's perceptions, it is not unreasonable to expect that there is no significant relationship between external motivation. And observe conceptual understanding. ===================================================================================== COPYRIGHTS ©2019 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers. ====================================================================================
Potencial de la inteligencia artificial para la detección temprana del melanoma maligno en Colombia
No full textLa Inteligencia Artificial (IA) en el campo médico de Colombia, especialmente en la detección temprana del melanoma, ofrece perspectivas transformadoras. La aplicación del Aprendizaje Automático y el Aprendizaje Profundo ha abierto nuevas posibilidades para el análisis detallado y complejo de datos. Dentro de estas técnicas, las Redes Neuronales Convolucionales (CNN) destacan por su potencial en la interpretación precisa de imágenes dermatológicas. Pero, a pesar de su alta precisión, estos sistemas podrían no abarcar completamente las sutilezas clínicas, desafiando el paradigma tradicional del diagnóstico basado en la experiencia y la empatía humanas.
Este estudio tiene como objetivo compilar información sobre el potencial de la Inteligencia Artificial para la detección temprana del melanoma maligno en Colombia, identificando los desafíos y oportunidades que enfrenta la implementación de estas herramientas avanzadas en la práctica clínica.
Esta monografía de compilación se relaciona con la aplicación de IA en la detección de melanoma en el contexto médico colombiano. Se recopiló información de diversas fuentes bibliográficas, incluyendo estudios académicos, páginas web y datos sobre el uso de herramientas de IA en el sector médico de Colombia.
Finalmente, con la biodiversidad y datos en Colombia, existe una oportunidad para mejorar y adaptar los modelos de Aprendizaje Automático y otras formas de IA para lograr un diagnóstico más preciso y efectivo del melanoma. Si bien existen desafíos, el interés del sector privado es un motivo para ser optimistas sobre el futuro de la implementación de la IA en el campo médico colombiano, especialmente en la detección temprana del melanoma.Artificial Intelligence (AI) in Colombia's medical field, especially in the early detection of melanoma, offers transformative perspectives. The application of Machine Learning and Deep Learning has opened new possibilities for detailed and complex data analysis. Within these techniques, Convolutional Neural Networks (CNN) stand out for their potential in the precise interpretation of dermatological images. But despite their high accuracy, these systems may not fully encompass clinical subtleties, challenging the traditional paradigm of diagnosis based on human experience and empathy.
This study aims to compile information on the potential of Artificial Intelligence for the early detection of malignant melanoma in Colombia, identifying the challenges and opportunities faced by the implementation of these advanced tools in clinical practice.
This compilation monograph is related to the application of AI in the detection of melanoma in the Colombian medical context. Information was collected from various bibliographic sources, including academic studies, web pages and data on the use of AI tools in the Colombian medical sector.
Finally, with the biodiversity and data in Colombia, there is an opportunity to improve and adapt Machine Learning models and other forms of AI to achieve more accurate and effective diagnosis of melanoma. While there are challenges, the interest of the private sector is a reason to be optimistic about the future of AI implementation in the Colombian medical field, especially in the early detection of melanoma.1. PLANTEAMIENTO DEL PROBLEMA.............................................. 121.1. Descripción del problema.......................................................... 122. JUSTIFICACIÓN............................................................................. 143. OBJETIVOS...................................................................................... 163.1. Objetivo General......................................................................... 163.2. Objetivos Específicos...................................................................... 164. METODOLOGÍA............................................................................ 174.1. Tipo de Estudio............................................................................. 174.2. Población..................................................................................... 174.3. Muestra......................................................................................... 174.4. Unidad de Análisis...................................................................... 184.5. Organización de la monografía.................................................. 184.6. Presentación de la Información................................................. 184.7. Aspectos éticos............................................................................. 184.8. Aspectos de propiedad intelectual y derechos de autor....... 195. MONOGRAFÍA.............................................................................. 205.1. RAMAS DE LA INTELIGENCIA ARTIFICIAL UTILIZADAS INTERNACIONALMENTE PARA LA DETECCIÓN TEMPRANA DEL MELANOMA MALIGNO........ 205.1.1. Aprendizaje Automático (Machine Learning-ML) como Rama Central de la IA ...................................................215.1.2. Aprendizaje Profundo (Depp Learning-DL)............................................................... 235.1.3. Redes Neuronales Convolucionales (CNNs)............................................................ 255.1.4. Aprendizaje por Refuerzo........................................................ 265.2. BARRERAS Y FACILITADORES PARA LA IMPLEMENTACIÓN DE INTELIGENCIA ARTIFICIAL EN LA DETECCIÓN TEMPRANA DEL MELANOMA MALIGNO EN COLOMBIA..... 305.2.1. IMPORTANCIA DE LA IMPLEMENTACIÓN DE LA INTELIGENCIA ARTIFICIAL EN LA DETECCIÓN TEMPRANA DEL MELANOMA MALIGNO EN EL SISTEMA DE SALUD COLOMBIANO...... 376. CONSIDERACIONES FINALES............................................................ 427. CONCLUSIONES.......................................................................... 458. RECOMENDACIONES.................................................................... 489. BIBLIOGRAFÍA.................................................................................. 51EspecializaciónEspecialista en Auditoria de la Calidad en SaludMonografía
