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Source channel @githubtrending · Post #15200 · Oct 6

#php#ehr#emr#fhir#global_health#health#healthcare#hit#international#linux#medical#medical_informatics#medical_information#medical_records#openemr#osx#php#practice_management#proprietary_counterparts#sponsors#windows OpenEMR is a free, open-source electronic health records (EHR) and medical practice management software that works on many platforms like Windows, Linux, and Mac. It offers features such as patient scheduling, electronic billing, integrated health records, and support for both outpatient and inpatient care. It supports modern standards like FHIR for easy and secure data sharing between healthcare providers. OpenEMR is highly customizable, allowing you to tailor it to your specific needs, and it is ONC certified, ensuring compliance with healthcare regulations. Using OpenEMR can save costs compared to paid EHRs and gives you control over your patient data while benefiting from a supportive community and free resources. https://github.com/openemr/openemr

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djangoproject

@djangoproject · Post #274 · 03/18/2017, 01:48 AM

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https://github.com/riga/tfdeploy Google's TensorFlow framework is taking off big-time now that it's at a full 1.0 release. One common question about it: How can I make use of the models I train in TensorFlow without using TensorFlow itself? #Tfdeploy is a partial answer to that question. It exports a trained TensorFlow model to "a simple #NumPy-based callable," meaning the model can be used in Python with Tfdeploy and the the NumPy math-and-stats library as the only dependencies. Most of the operations you can perform in TensorFlow can also be performed in Tfdeploy, and you can extend the behaviors of the library by way of standard Python metaphors (such as overloading a class). Now the bad news: Tfdeploy doesn't support GPU acceleration, if only because NumPy doesn't do that. Tfdeploy's creator suggests using the gNumPy project as a possible replacement. #Machine_learning

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