Système intelligent de diagnostic clinique des maladies dentaires utilisant la programmation parallèle dans les threads et les automates pour la validation sémantique, en tant qu'aide à la décision pour les spécialistes de la santé.
Palabras clave:
Diagnostic dentaire automatisé, intelligence artificielle en santé, validation sémantique clinique, traitement parallèle en diagnosticResumen
Ce projet présente une solution innovante pour le diagnostic dentaire automatisé, visant à optimiser la précision clinique, la traçabilité des documents et l'efficacité opérationnelle grâce au traitement structuré des symptômes et à la validation sémantique basée sur des modèles informatiques formels. Son impact réside dans la réduction des erreurs humaines, la standardisation de l'analyse clinique et l'amélioration de la qualité des comptes rendus de diagnostic, consolidant ainsi un modèle intelligent applicable en situation réelle. Dans ce contexte, le diagnostic traditionnel présente des limites dues à la subjectivité, à la faible reproductibilité et à la variabilité des critères entre professionnels. Ces limites affectent la fiabilité clinique, tandis que l'intelligence artificielle s'est révélée un outil efficace pour l'interprétation des symptômes et des radiographies, intégrant les informations cliniques dans des comptes rendus structurés et vérifiables. En Colombie, le développement de solutions automatisées pour le dépistage et l'orientation diagnostique offre un contexte favorable à l'adoption de systèmes intelligents en santé bucco-dentaire. L'objectif du projet est de développer un système intelligent de diagnostic dentaire automatisé, avec traçabilité technique, validation structurée et traitement parallèle, capable de corréler les descriptions des symptômes et les preuves visuelles grâce à des algorithmes de validation sémantique et à une analyse simultanée. La méthodologie a été structurée en cinq phases selon l'approche agile Scrum : analyse des exigences cliniques et informatiques, développement du module de symptômes, conception de l'interface de diagnostic, implémentation des composants d'exportation et d'audit des documents, et validation par simulation selon des critères cliniques. Les données utilisées proviennent de bases de données scientifiques structurées, d'ensembles cliniques symptomatiques et de simulations radiographiques validées, garantissant leur représentativité et leur cohérence technique. Les résultats démontrent un système capable de traiter les symptômes en langage naturel, de les corréler aux images et de générer des diagnostics structurés au format PDF, avec un taux de concordance supérieur à 92 %, des temps de réponse inférieurs à trois secondes par requête et une validation sémantique complète. En conclusion, le système présente une grande viabilité technique et clinique, offrant un outil robuste et évolutif, en phase avec les politiques de transformation numérique en santé bucco-dentaire.
Referencias
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