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author Atsou, Kueshivi Midodji
Rachet, Bernard
Maringe, Camille
Cornet, Edouard
Chretien, Marie Lorraine
Rossi, Cedric
Remontet, Laurent
Roche, Laurent
Giorgi, Roch
Gauthier, Sophie
Girard, Stéphanie
Böckle, Johann
Wasse, Stephane
Rachou, Hélène
Bouzid, Laila
Poncet, Jean-Marc
Orazio, Sébastien
Monnereau, Alain
Troussard, Xavier
Maynadie, Marc
author_facet Atsou, Kueshivi Midodji
Rachet, Bernard
Maringe, Camille
Cornet, Edouard
Chretien, Marie Lorraine
Rossi, Cedric
Remontet, Laurent
Roche, Laurent
Giorgi, Roch
Gauthier, Sophie
Girard, Stéphanie
Böckle, Johann
Wasse, Stephane
Rachou, Hélène
Bouzid, Laila
Poncet, Jean-Marc
Orazio, Sébastien
Monnereau, Alain
Troussard, Xavier
Maynadie, Marc
author_sort Atsou, Kueshivi Midodji
collection PubMed
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publishDate 2023
publisher Lippincott Williams & Wilkins
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spelling pubmed-104303562023-08-17 PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY Atsou, Kueshivi Midodji Rachet, Bernard Maringe, Camille Cornet, Edouard Chretien, Marie Lorraine Rossi, Cedric Remontet, Laurent Roche, Laurent Giorgi, Roch Gauthier, Sophie Girard, Stéphanie Böckle, Johann Wasse, Stephane Rachou, Hélène Bouzid, Laila Poncet, Jean-Marc Orazio, Sébastien Monnereau, Alain Troussard, Xavier Maynadie, Marc Hemasphere Publication Only Lippincott Williams & Wilkins 2023-08-08 /pmc/articles/PMC10430356/ http://dx.doi.org/10.1097/01.HS9.0000974256.32999.b9 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access Abstract Book distributed under the Attribution-NonCommercial-NoDerivs (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) which allows third parties to download the articles and share them with others as long as they credit the author and the Abstract Book, but they cannot change the content in any way or use them commercially.
spellingShingle Publication Only
Atsou, Kueshivi Midodji
Rachet, Bernard
Maringe, Camille
Cornet, Edouard
Chretien, Marie Lorraine
Rossi, Cedric
Remontet, Laurent
Roche, Laurent
Giorgi, Roch
Gauthier, Sophie
Girard, Stéphanie
Böckle, Johann
Wasse, Stephane
Rachou, Hélène
Bouzid, Laila
Poncet, Jean-Marc
Orazio, Sébastien
Monnereau, Alain
Troussard, Xavier
Maynadie, Marc
PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title_full PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title_fullStr PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title_full_unstemmed PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title_short PB1855: USE OF MACHINE LEARNING MODEL TO IDENTIFY PATIENTS RECEIVING OPTIMAL TREATMENT AND THE ASSOCIATED NON-BIOLOGICAL FACTORS: A POPULATION-BASED STUDY
title_sort pb1855: use of machine learning model to identify patients receiving optimal treatment and the associated non-biological factors: a population-based study
topic Publication Only
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10430356/
http://dx.doi.org/10.1097/01.HS9.0000974256.32999.b9
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