Found: 9
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Semisupervised Deep Learning Techniques for Predicting Acute Respiratory Distress Syndrome From Time-Series Clinical Data: Model Development and Validation Study.
- Published in:
- JMIR Formative Research, 2021, v. 5, n. 9, p. 1, doi. 10.2196/28028
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- Publication type:
- Article
Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction.
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- Health Informatics Journal, 2020, v. 26, n. 3, p. 1912, doi. 10.1177/1460458219894494
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- Article
A Machine Learning Approach to Predict Deep Venous Thrombosis Among Hospitalized Patients.
- Published in:
- Clinical & Applied Thrombosis/Hemostasis, 2021, v. 27, p. 1, doi. 10.1177/1076029621991185
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- Article
Widespread nitrogen fixation in sediments from diverse deep‐sea sites of elevated carbon loading.
- Published in:
- Environmental Microbiology, 2018, v. 20, n. 12, p. 4281, doi. 10.1111/1462-2920.14342
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- Publication type:
- Article
Heavy water and <sup>15</sup> N labelling with Nano SIMS analysis reveals growth rate-dependent metabolic heterogeneity in chemostats.
- Published in:
- Environmental Microbiology, 2015, v. 17, n. 7, p. 2542, doi. 10.1111/1462-2920.12752
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- Publication type:
- Article
Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis.
- Published in:
- JGH Open, 2022, v. 6, n. 3, p. 196, doi. 10.1002/jgh3.12716
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- Publication type:
- Article
Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial.
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- Journal of Clinical Medicine, 2020, v. 9, n. 12, p. 3834, doi. 10.3390/jcm9123834
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- Article
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from 461 US hospitals.
- Published in:
- 2020
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- Publication type:
- journal article
Enriching the Study Population for Ischemic Stroke Therapeutic Trials Using a Machine Learning Algorithm.
- Published in:
- Frontiers in Neurology, 2022, v. 12, p. 1, doi. 10.3389/fneur.2021.784250
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- Publication type:
- Article