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Starting with good data is critical for medical applications of A.I. and machine learning.
Correct interpretation of tracer test data is critical for understanding transport processes in the subsurface.
Utilizing building energy usage data is critical for the successful deployment of energy efficiency.
Accurate loss coefficient data is critical for energy efficient hydraulic design.
Assessing the trustworthiness of sensor data and transmitters of this data is critical for quality assurance.
Connectivity is critical for care transformation, and data is critical for connectivity, so until these public rates are transparent, Americans will continue to be shortchanged.
Similar(22)
Historical climate data are critical for investment planning, particularly in regions where climate is changing rapidly.
The flow network data are critical for important uses such as flood forecasting and watershed management.
High-quality and standardized clinical data are critical for patient registries which requires the systematic use of ontologies such as the HPO (see above).
Such data are critical for the design of new molecules for stabilizing mineral floc dispersions and for assessing the mobility of CMC-coated particles in the subsurface.
Real-time, high quality data are critical for emergency medical applications, telemedicine, and preventive care, which sensor based applications can provide.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com