Sobre las barreras posibles para que el conocimiento sea accionable, valoro que desde el 2020 a la fecha han existido avances significativos en cuanto al acceso a datos -abiertos-, así como herramientas de trabajo para lograr avances significativos en la formación profesional y académica. Pero, ya abordar datos clínicos o de laboratorio, están sujetos a protocolos que implican los aspectos anteriores, aunado los contextos de la entidad donde se desempeña. Es decir, el tipo de infraestructura, personal cualificado que disponga de todos los elementos para el acceso a datos, clasificación y procesamiento, así como el diseño de modelos para lograr determinados objetivos, muchos de estos, a la medida... sin dejar de mencionar la activación del manejo de los protocolos y el abordaje ético.
El latente sesgo implica por tanto, atender aspectos en el proceso ya complejo en los sistemas biológicos, la cualificación para hacerle frente a la cantidad y calidad de los datos, y la implementación de los modelos, algunos muy idealistas, reiterar que la mayoría se desarrolla a la medida, incrementando la complejidad productiva... el asunto ético está presente: acceso a datos, manipulación, volumen significativo para eliminar ruidos, realizar pares, contrastes, constatar comportamientos, variabilidades, etc.
Regarding the possible barriers for knowledge to be actionable, I believe that since 2020 to date there have been significant advances in terms of access to open data, as well as work tools to achieve significant advances in professional and academic training. However, whether clinical or laboratory data are addressed, they are subject to protocols that involve the above aspects, together with the contexts of the entity where they work. That is to say, the type of infrastructure, qualified personnel who have all the elements for data access, classification and processing, as well as the design of models to achieve certain objectives, many of these, tailor-made... not to mention the activation of the management of protocols and the ethical approach.
The latent bias therefore implies attending to aspects in the already complex process in biological systems, the qualification to cope with the quantity and quality of data, and the implementation of models, some very idealistic, reiterating that most of them are developed to measure, increasing the productive complexity... the ethical issue is present: access to data, manipulation, significant volume to eliminate noise, make pairs, contrasts, verify behaviors, variabilities, etc.
El latente sesgo implica por tanto, atender aspectos en el proceso ya complejo en los sistemas biológicos, la cualificación para hacerle frente a la cantidad y calidad de los datos, y la implementación de los modelos, algunos muy idealistas, reiterar que la mayoría se desarrolla a la medida, incrementando la complejidad productiva... el asunto ético está presente: acceso a datos, manipulación, volumen significativo para eliminar ruidos, realizar pares, contrastes, constatar comportamientos, variabilidades, etc.
Regarding the possible barriers for knowledge to be actionable, I believe that since 2020 to date there have been significant advances in terms of access to open data, as well as work tools to achieve significant advances in professional and academic training. However, whether clinical or laboratory data are addressed, they are subject to protocols that involve the above aspects, together with the contexts of the entity where they work. That is to say, the type of infrastructure, qualified personnel who have all the elements for data access, classification and processing, as well as the design of models to achieve certain objectives, many of these, tailor-made... not to mention the activation of the management of protocols and the ethical approach.
The latent bias therefore implies attending to aspects in the already complex process in biological systems, the qualification to cope with the quantity and quality of data, and the implementation of models, some very idealistic, reiterating that most of them are developed to measure, increasing the productive complexity... the ethical issue is present: access to data, manipulation, significant volume to eliminate noise, make pairs, contrasts, verify behaviors, variabilities, etc.
