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Riccardo Miotto

Showing results (1-10 of 47) with videos related to

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Journal of the American Medical Informatics Association : JAMIA|March 15, 2015
Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trialsRiccardo Miotto, Chunhua Weng
Journal of Biomedical Informatics|September 17, 2013
Unsupervised mining of frequent tags for clinical eligibility text indexingRiccardo Miotto, Chunhua Weng
AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science|December 5, 2013
Towards dynamic and interactive retrieval of clinical trials using common eligibility featuresRiccardo Miotto, Chunhua Weng
Clinical Journal of the American Society of Nephrology : CJASN|February 3, 2023
Deep Learning in MedicineSamuel P Heilbroner, Riccardo Miotto
Journal of Biomedical Informatics|August 7, 2013
eTACTS: a method for dynamically filtering clinical trial search resultsRiccardo Miotto, Silis Jiang, Chunhua Weng
JAMIA Open|November 27, 2018
Trends in anesthesiology research: a machine learning approach to theme discovery and summarizationAlexander Rusanov, Riccardo Miotto, Chunhua Weng
Journal of Biomedical Informatics|August 1, 2012
A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteriaZhihui Luo, Riccardo Miotto, Chunhua Weng
Studies in Health Technology and Informatics|August 8, 2013
A method for probing disease relatedness using common clinical eligibility criteriaMary Regina Boland, Riccardo Miotto, Chunhua Weng
Scientific Reports|May 18, 2016
Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health RecordsRiccardo Miotto, Li Li, Brian A Kidd, et al.
Briefings in Bioinformatics|May 9, 2017
Deep learning for healthcare: review, opportunities and challengesRiccardo Miotto, Fei Wang, Shuang Wang, et al.
Pageof 5

Showing results (1-10 of 47) with videos related to

Sort By:
Pageof 5
Journal of the American Medical Informatics Association : JAMIA|March 15, 2015
Case-based reasoning using electronic health records efficiently identifies eligible patients for clinical trialsRiccardo Miotto, Chunhua Weng
Journal of Biomedical Informatics|September 17, 2013
Unsupervised mining of frequent tags for clinical eligibility text indexingRiccardo Miotto, Chunhua Weng
AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science|December 5, 2013
Towards dynamic and interactive retrieval of clinical trials using common eligibility featuresRiccardo Miotto, Chunhua Weng
Clinical Journal of the American Society of Nephrology : CJASN|February 3, 2023
Deep Learning in MedicineSamuel P Heilbroner, Riccardo Miotto
Journal of Biomedical Informatics|August 7, 2013
eTACTS: a method for dynamically filtering clinical trial search resultsRiccardo Miotto, Silis Jiang, Chunhua Weng
JAMIA Open|November 27, 2018
Trends in anesthesiology research: a machine learning approach to theme discovery and summarizationAlexander Rusanov, Riccardo Miotto, Chunhua Weng
Journal of Biomedical Informatics|August 1, 2012
A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteriaZhihui Luo, Riccardo Miotto, Chunhua Weng
Studies in Health Technology and Informatics|August 8, 2013
A method for probing disease relatedness using common clinical eligibility criteriaMary Regina Boland, Riccardo Miotto, Chunhua Weng
Scientific Reports|May 18, 2016
Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health RecordsRiccardo Miotto, Li Li, Brian A Kidd, et al.
Briefings in Bioinformatics|May 9, 2017
Deep learning for healthcare: review, opportunities and challengesRiccardo Miotto, Fei Wang, Shuang Wang, et al.
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