Search Results - Boussios, Costas

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  1. 1
    A new approach to identifying patients with elevated risk for Fabry disease using a machine learning algorithm

    A new approach to identifying patients with elevated risk for Fabry disease using a machine learning algorithm by Jefferies, John L, Spencer, Alison K, Lau, Heather A, Nelson, Matthew W, Giuliano, Joseph D, Zabinski, Joseph W, Boussios, Costas, Curhan, Gary, Gliklich, Richard E, Warnock, David G

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  2. 2
    Validation of a machine learning approach to estimate expanded disability status scale scores for multiple sclerosis

    Validation of a machine learning approach to estimate expanded disability status scale scores for multiple sclerosis by Alves, Pedro, Green, Eric, Leavy, Michelle, Friedler, Haley, Curhan, Gary, Marci, Carl, Boussios, Costas

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  3. 3
    Reply to Letter to the Editor: Machine learning to deal with missing disability status

    Reply to Letter to the Editor: Machine learning to deal with missing disability status by Alves, Pedro, Leavy, Michelle, Curhan, Gary, Marci, Carl, Boussios, Costas

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  4. 4
    Validation of a machine learning approach to estimate Systemic Lupus Erythematosus Disease Activity Index score categories and application in a real-world dataset

    Validation of a machine learning approach to estimate Systemic Lupus Erythematosus Disease Activity Index score categories and application in a real-world dataset by Alves, Pedro, Bandaria, Jigar, Leavy, Michelle B, Gliklich, Benjamin, Boussios, Costas, Su, Zhaohui, Curhan, Gary

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  5. 5
    Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis

    Validation of a machine learning approach to estimate Clinical Disease Activity Index Scores for rheumatoid arthritis by Spencer, Alison K., Bandaria, Jigar, Leavy, Michelle B., Gliklich, Benjamin, Su, Zhaohui, Curhan, Gary, Boussios, Costas

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  6. 6
    TOP-309 Identifying patient characteristics associated with the risk of long-term liver and cardiovascular outcomes and high healthcare costs in metabolic dysfunction-associated steatohepatitis: a retrospective cohort analysis using an artificial intelligence model

    TOP-309 Identifying patient characteristics associated with the risk of long-term liver and cardiovascular outcomes and high healthcare costs in metabolic dysfunction-associated st... by Mangla, Kamal Kant, Gbadamosi, Semiu, Semeniuta, Daniel, Soule, Benjamin, Nordahl, Helene, Bandaria, Jigar, Zabinski, Joseph, Curhan, Gary, Boussios, Costas

    Published in Journal of hepatology
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  7. 7
    A HIGHLY PREDICTIVE MACHINE LEARNING MODEL TO IDENTIFY HOSPITALIZED PATIENTS AT RISK FOR 30-DAY READMISSION OR MORTALITY

    A HIGHLY PREDICTIVE MACHINE LEARNING MODEL TO IDENTIFY HOSPITALIZED PATIENTS AT RISK FOR 30-DAY READMISSION OR MORTALITY by Su, Zhaohui, Donadio, Gregory, Brecht, Tom, O'Donovan, Francis, Boussios, Costas, Menon, Vandana, Gliklich, Rich

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  8. 8
    Estimation of arrhythmia risk in patients with Fabry disease using a machine learning model

    Estimation of arrhythmia risk in patients with Fabry disease using a machine learning model by Aguiar, Patricio, Biondetti, Giorgio Pietro, Warnock, David G., Kallish, Staci, Nelson, Matthew W., Giuliano, Joseph, Zabinski, Joseph W., Boussios, Costas, Curhan, Gary, Bandaria, Jigar N., Gliklich, Richard E., Jefferies, John L.

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  9. 9
    Estimation of stroke risk in patients with Fabry disease using a machine learning model

    Estimation of stroke risk in patients with Fabry disease using a machine learning model by Kallish, Staci, Biondetti, Giorgio Pietro, Jefferies, John L., Aguiar, Patricio, Nelson, Matthew W., Giuliano, Joseph, Zabinski, Joseph W., Boussios, Costas, Curhan, Gary, Bandaria, Jigar N., Gliklich, Richard E., Warnock, David G.

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  10. 10
    Utilization of artificial intelligence to identify undiagnosed Fabry patients: Development of a validated machine learning model

    Utilization of artificial intelligence to identify undiagnosed Fabry patients: Development of a validated machine learning model by Jefferies, John L., Spencer, Alison K., Warnock, David G., Lau, Heather A., Nelson, Matthew W., Giuliano, Joseph D., Zabinski, Joseph W., Boussios, Costas, Curhan, Gary, Bandaria, Jigar N., Gliklich, Richard E.

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