Q:
Tensorflow model saved as binary file
I have a tensorflow model saved as.pb file (using the SavedModelBuilder class and saving it using the SavedModel.save function).
Is there a way to read this file and load it in the same framework and use it?
What I mean is:
from tensorflow.contrib.saved_model.loader_impl import SavedModelImporter
importer = SavedModelImporter(filename)
Then I can use the function to_proto, to export the model, and then load the tensorflow model with the function load_pb.
The code for export and import functions is from the
A:
You can pass SavedModelImporter the saved model filename to use.
If it is a python file, you can open the file to read the content.
[Retrospective analysis of acute heart failure admissions in a public hospital in 2015].
Acute heart failure is a frequent admission in cardiovascular services, which, because of its high mortality and high economic impact, has significant social and health care costs. To describe the epidemiological and clinical profile of heart failure admissions in the Public Health Service (PHS) of São Paulo State in 2015. Descriptive, retrospective study based on hospitalization records from 2015 in the PHS of São Paulo State. The data collection included demographic data, comorbidities, reason for admission, length of hospitalization and in-hospital death. Descriptive statistics were calculated, and variables were expressed in absolute and relative frequencies. In 2015, there were 3,942 hospitalizations due to heart failure, representing an average annual rate of 26.7 cases/million inhabitants. The mean age of patients was 70 years (SD 17.5), and they were predominantly male (n=2,407, 61%). Most of them had chronic conditions (n=3,336; 87%), with hypertension and ischemic heart disease as the most prevalent. The mean length of hospitalization was 9 days. The in-hospital death rate was 4.3% (n=181). A total of 711 (18.7%) patients were readmitted during their hospitalization, and the median time of the first readmission was 9
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