RESUMO
La inteligencia artificial tiene el potencial de transformar la forma en que se brinda la atención médica. Puede respaldar mejoras en los resultados y aumentar la productividad y la eficiencia de la prestación de los servicios. En servicios de las diferentes especialidades los avances realizados a nivel hardware deben desarrollarse en paralelo con los métodos de aprendizaje automático, aspectos que la inteligencia artificial contribuye para promover un cambio de paradigma significativo en las más diversas áreas de la medicina. Es importante en la educación médica como eje para el conocimiento y en la toma de decisiones que pueden mejorar el desempeño de los profesionales. Los estudiantes de medicina de nueva generación pueden adaptarse perfectamente a los nuevos métodos digitalizados en un contexto médico globalizado, incluida la inteligencia artificial. Por ello es importante tener como objetivos a implementar en los planes de estudio e introducir programas educativos representativos de esta tecnología. Es fundamental que todas las áreas del Sistema de Salud tengan confianza en los sistemas informáticos específicamente en el aprendizaje profundo, no solo por la información concreta y objetiva que de él se deriva sino también por la posibilidad de predecir eventos futuros, brindando alta certeza en cuanto al diagnóstico y tratamiento de enfermedades.
Artificial intelligence has the potential to transform the way healthcare is delivered. You can support improved results and increase the productivity and efficiency of service delivery. In the services of the different specialties, the advances made at the hardware level must be developed in parallel with the methods of machine learning, aspects that artificial intelligence contributes to promote a significant paradigm shift in the most diverse areas of medicine. It is important in medical education as an axis for knowledge and in making decisions that can improve the performance of professionals. New generation medical students can perfectly adapt to new digitized methods in a globalized medical context, including artificial intelligence. For this reason, it is important to have as objectives to be implemented in the study plans and to introduce educational programs that are representative of this technology. It is essential that all areas of the Health System have confidence in computer systems specifically in deep learning, not only because of the concrete and objective information that is derived from it but also because of the possibility of predicting future events, providing high certainty regarding to the diagnosis and treatment of diseases.
Assuntos
Tecnologia , Inteligência Artificial , Educação Médica , Cuidados Médicos , DiagnósticoRESUMO
La actualidad está marcada por el desarrollo cada vez más vertiginoso de la tecnología. Este hecho incide necesariamente en el proceso formativo de nuestros estudiantes Los EVA (entornos virtuales del aprendizaje) son herramientas para facilitar la transmisión del conocimiento mediado por la informática.
Assuntos
Ciências da Saúde/educação , Aprendizagem Baseada em Problemas , Educação a DistânciaRESUMO
This article discusses the development of the first regional computerized database for the epidemiological evaluation of maxillofacial trauma and tests its usefulness by evaluating the appropriateness and completeness of the resulting information.The database was developed using Microsoft Access, implemented using Visual Basic. Data were entered in the database by 4 different maxillofacial specialists, one from each of the 4 main regional hospitals where maxillofacial trauma is treated. Clinical information was taken from 100 complete records of patients hospitalized for maxillofacial fractures at the Maxillofacial Division of San Giovanni Battista Hospital in Turin from January to June 2009.Thirteen database fields were used: general information, cause and mechanism of injury, fracture site, Facial Injury Severity Scale, head and neck examination, associated injuries, timing and type of surgery, and days of hospitalization.Overall, the data entered were 99.45% complete and 99.5% accurate. Thus, our regional maxillofacial database can be considered complete and accurate. Some of the errors, mainly in the fields "fracture site" and "Facial Injury Severity Scale," were attributable to an incorrect interpretation of facial fracture diagnoses, based on the medical records that were provided.
