21 results on '"Steven R Steinhubl"'
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2. Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias.
3. Educating the healthcare workforce of the future: lessons learned from the development and implementation of a 'Wearables in Healthcare' course.
4. A Comprehensive Explanation Framework for Biomedical Time Series Classification.
5. Inter-individual variation in objective measure of reactogenicity following COVID-19 vaccination via smartwatches and fitness bands.
6. Wearable sensor derived decompensation index for continuous remote monitoring of COVID-19 diagnosed patients.
7. Passive detection of COVID-19 with wearable sensors and explainable machine learning algorithms.
8. On the Effectiveness of Deep Representation Learning: The Atrial Fibrillation Case.
9. Home Monitoring of Blood Pressure: Short-Term Changes During Serial Measurements for 56398 Subjects.
10. Digitizing clinical trials.
11. Early detection of heart failure with varying prediction windows by structured and unstructured data in electronic health records.
12. Digital clinical trials: creating a vision for the future.
13. Analytics Pipeline for Left Ventricle Segmentation and Volume Estimation on Cardiac MRI Using Deep Learning.
14. The Healthy Pregnancy Research Program: transforming pregnancy research through a ResearchKit app.
15. Digital medicine, on its way to being just plain medicine.
16. Data Driven Modeling of Electronic Health Record Data to Detect Pre-Diagnostic Heart Failure Subtypes in Primary Care.
17. Characterizing Physicians Practice Phenotype from Unstructured Electronic Health Records.
18. Limestone: High-throughput candidate phenotype generation via tensor factorization.
19. PARAMO: A PARAllel predictive MOdeling platform for healthcare analytic research using electronic health records.
20. Automatic identification of heart failure diagnostic criteria, using text analysis of clinical notes from electronic health records.
21. Early Detection of Heart Failure using Data Driven Modeling Approaches on Electronic Health Records: How far can one go without Domain Knowledge?
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