Examinando por Materia "Procesamiento del lenguaje natural"
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Publicación Agente de inteligencia artificial para el apoyo a la primera impresión diagnóstica a partir de descripciones sintomáticas expresadas en lenguaje natural(Universidad EAFIT, 2025-11-24) Bertel Morales, Juan Pablo; Jaramillo Múnera, Yomin EstivenThis thesis proposes the development of an artificial intelligence (AI) agent capable of supporting the generation of an initial diagnostic impression based on symptoms expressed in natural language. The project is grounded in the recognition that medical diagnosis is a complex task prone to errors, particularly when it relies on subjective and unstructured descriptions. To support clinical decision-making, natural language processing and machine learning techniques were applied following the CRISP-DM methodology. The model was trained using the synthetic DDxPlus dataset, which enabled the simulation of clinical scenarios without compromising real patient information. In the process, symptoms were transformed into synthetic anamneses through semantic normalization and subsequently vectorized using various biomedical embedding models. These representations were then used to train a supervised model tasked with associating each narrative with the confirmed diagnosis. As an additional evaluation, a “stress test” was conducted in a simulated environment, in which a healthcare professional interacted directly with the system to assess its ability to interpret real symptomatic descriptions and generate preliminary diagnostic suggestions in a coherent, consistent, and safe.Ítem Los modelos verbales en lenguaje natural y su utilización en la elaboración de esquemas conceptuales para el desarrollo de software: una revisión crítica(Universidad EAFIT, 2005) Zapata Jaramillo, Carlos Mario; Arango Isaza, Fernando; Facultad de Minas de la Universidad Nacional de MedellínPublicación Procesamiento de lenguaje natural en el sector de BPO en Colombia(Universidad EAFIT, 2021) Jiménez Cardona, Daniel; Acosta Mejía, Camilo AndrésOne of the most important fields of artificial intelligence in recent years is natural language processing. This article explains its operation and a cost analysis using GPT-3, one of the most important AIs. In addition, based on data on working conditions, the possible effects on the Colombian labor market, specifically the Bussines Process Outsourcing (BPO) sector, are studied. Finally, it is found that the profitability of migrating to the automation of these activities is high and, in addition, the government provides incentives for change. However, the labour market is not prepared to absorb the impact, so it is important that the Ministry of ICT and the Ministry of Education work together so that automation is not a problem in the future of social welfare.Publicación Sistema multi-agente para la preselección de candidatos en vacantes públicas de empleo utilizando inteligencia artificial generativa(Universidad EAFIT, 2025) Blandón Londoño, Cristian Mauricio; Álvarez Barrera, Claudia Patricia; Martínez Vargas, Juan DavidHistorically, recruitment processes have been carried out manually. In such processes, candidates go through a series of filters that vary depending on the specific requirements of each vacancy. As these procedures are not standardized, their duration can be extended, leading to an increase in unfilled positions and, consequently, negatively impacting organizational competitiveness. Identifying the ideal candidate for a job vacancy is a task that demands both time and resources. Today, this represents a significant challenge for organizations within the Human Resources sector, where each day spent searching for the right talent translates into operational costs. As a result, delays in recruitment activities directly affect the achievement of strategic organizational goals. Despite the growing adoption of Applicant Tracking Systems (ATS), these tools often face semantic limitations and do not easily adapt to local contexts—especially in countries like Colombia, where a significant portion of the population is employed informally. This reality hinders not only the objective assessment of candidate suitability but also increases the likelihood of evaluative biases. Recent studies have begun exploring the integration of multi-agent architectures with Large Language Models (LLMs) to automate pre-screening processes. In line with this, the present project proposes the implementation of a multi-agent system for candidate evaluation. By combining Natural Language Processing (NLP) techniques with LLMs, the system aims to analyze applicant and job posting data to support human resources professionals in determining candidate-job fit. The system will be designed to optimize evaluation procedures in recruitment, with the goal of reducing the average time required for candidate assessment and selection. Furthermore, implementation seeks to minimize manual operations and mitigate bias in the evaluation process, thereby contributing to the sustainable development of human capital. It is anticipated that this solution will increase the efficiency of recruitment workflows and promote greater alignment between the skills demanded by employers and those offered in the labor market. This, in turn, is expected to benefit both employers and job seekers, and indirectly support efforts to bridge the skills gap in the Colombian labor market—particularly in a context characterized by high levels of informality—by establishing fair and competency-based evaluation criteria.