Medical diagnosis with neural networks
DOI:
https://doi.org/10.29059/cie.v2.1.31Keywords:
inteligencia artificial, redes neuronales artificiales, diagn´óstico médico, telemedicina, predicción de enfermedadesAbstract
Artificial intelligence, through the use of artificial neural networks, has become a relevant tool in the transformation of diagnostic and predictive processes in contemporary medicine. This study analyzes the application of artificial neural networks for disease prediction and diagnostic support, as well as their integration with telemedicine platforms. Using a structured methodology that includes data collection, preprocessing and feature selection, neural model design and training, validation, and continuous monitoring, significant improvements were identified in the early detection of complex diseases and in clinical risk stratification. The results demonstrate a reduction in errors associated with human factors, improved personalization of treatments, and optimization of healthcare resource utilization. In addition, the developed systems showed potential for continuous patient monitoring and dynamic adaptation of clinical recommendations. Nevertheless, the study highlights the need for ongoing validation and ethical, responsible integration to ensure clinical effectiveness and safety.
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Accepted 2026-04-05
Published 2026-04-30
