Published on in Vol 10, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35307, first published .
Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study

Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study

Predicting 30-Day Readmission Risk for Patients With Chronic Obstructive Pulmonary Disease Through a Federated Machine Learning Architecture on Findable, Accessible, Interoperable, and Reusable (FAIR) Data: Development and Validation Study

New JMIR MedInform: Predicting 30-Day Readmission Risk for #patients With Chronic Obstructive Pulmonary Disease Thr… https://t.co/36wHHAvPn8

3:09 PM · Jun 02, 2022

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RT @jmirpub: New JMIR MedInform: Predicting 30-Day Readmission Risk for #patients With Chronic Obstructive Pulmonary Disease Through a Fede…

3:09 PM · Jun 02, 2022

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RT @jmirpub: New JMIR MedInform: Predicting 30-Day Readmission Risk for #patients With Chronic Obstructive Pulmonary Disease Through a Fede…

3:09 PM · Jun 02, 2022

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