Feature selection and prediction of treatment failure in tuberculosis von Sauer, Christopher Martin, Sasson, David, Paik, Kenneth E, McCague, Ned, Celi, Leo Anthony, Sánchez Fernández, Iván, Illigens, Ben M W

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Vital lessons from struggling partnerships and potential partnerships: an international study with leaders across the health sector von Zwisler, Greg, Sauer, Christopher Martin, Shoultz, David

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Leveraging Machine Learning to Identify Subgroups of Misclassified Patients in the Emergency Department: Multicenter Proof-of-Concept Study von Wyatt, Sage, Lunde Markussen, Dagfinn, Haizoune, Mounir, Vestbø, Anders Strand, Sima, Yeneabeba Tilahun, Sandboe, Maria Ilene, Landschulze, Marcus, Bartsch, Hauke, Sauer, Christopher Martin

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Establishing Medical Intelligence-Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study von Brehmer, Alexander, Sauer, Christopher Martin, Salazar Rodríguez, Jayson, Herrmann, Kelsey, Kim, Moon, Keyl, Julius, Bahnsen, Fin Hendrik, Frank, Benedikt, Köhrmann, Martin, Rassaf, Tienush, Mahabadi, Amir-Abbas, Hadaschik, Boris, Darr, Christopher, Herrmann, Ken, Tan, Susanne, Buer, Jan, Brenner, Thorsten, Reinhardt, Hans Christian, Nensa, Felix, Gertz, Michael, Egger, Jan, Kleesiek, Jens

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Improved Survival of Cancer Patients Admitted to the Intensive Care Unit between 2002 and 2011 at a U.S. Teaching Hospital von Sauer, Christopher Martin, Dong, Jinghui, Celi, Leo Anthony, Ramazzotti, Daniele

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Neuroendocrine Key Regulator Gene Expression in Merkel Cell Carcinoma von Chteinberg, Emil, Sauer, Christopher Martin, Rennspiess, Dorit, Beumers, Lukas, Schiffelers, Lisa, Eben, Jonathan, Haugg, Anke, Winnepenninckx, Véronique, Kurz, Anna Kordelia, Speel, Ernst-Jan, Zenke, Martin, zur Hausen, Axel

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Why federated learning will do little to overcome the deeply embedded biases in clinical medicine von Sauer, Christopher Martin, Pucher, Gernot, Celi, Leo Anthony

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Impact of life-sustaining therapies on critically ill patients with cancer von Shah, Kanan, Matos, Joao, Struja, Tristan, Svoboda, Josef, Celi, Leo, Sauer, Christopher Martin

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Boosting Clinical Decision-making: Machine Learning for Intensive Care Unit Discharge von Cosgriff, Christopher Vincent, Celi, Leo Anthony, Sauer, Christopher Martin

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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis von Pucher, Gernot, Rostalski, Till, Nensa, Felix, Kleesiek, Jens, Reinhardt, Hans Christian, Sauer, Christopher Martin

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Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis... von Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer

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Feature Selection and Prediction of Treatment Failure in Tuberculosis von Sauer, Christopher Martin, Sasson, David, Paik, Kenneth E, McCague, Ned, Celi, Leo Anthony, Sanchez Fernandez, Ivan, Illigens, Ben

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Neuroendocrine Key Regulator Gene Expression in Merkel Cell Carcinoma12345 von Chteinberg, Emil, Sauer, Christopher Martin, Rennspiess, Dorit, Beumers, Lukas, Schiffelers, Lisa, Eben, Jonathan, Haugg, Anke, Winnepenninckx, Véronique, Kurz, Anna Kordelia, Speel, Ernst-Jan, Zenke, Martin, zur Hausen, Axel

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Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients von Dauvin, Antonin, Donado, Carolina, Bachtiger, Patrik, Huang, Ke-Chun, Sauer, Christopher Martin, Ramazzotti, Daniele, Bonvini, Matteo, Celi, Leo Anthony, Douglas, Molly J.

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Long-term follow-up of IPEX syndrome patients after different therapeutic strategies: An international multicenter retrospective study von Barzaghi, Federica, Amaya Hernandez, Laura Cristina, Neven, Benedicte, Ricci, Silvia, Kucuk, Zeynep Yesim, Bleesing, Jack J., Nademi, Zohreh, Slatter, Mary Anne, Ulloa, Erlinda Rose, Shcherbina, Anna, Roppelt, Anna, Worth, Austen, Silva, Juliana, Aiuti, Alessandro, Murguia-Favela, Luis, Speckmann, Carsten, Carneiro-Sampaio, Magda, Fernandes, Juliana Folloni, Baris, Safa, Ozen, Ahmet, Karakoc-Aydiner, Elif, Kiykim, Ayca, Schulz, Ansgar, Steinmann, Sandra, Notarangelo, Lucia Dora, Gambineri, Eleonora, Lionetti, Paolo, Shearer, William Thomas, Forbes, Lisa R., Martinez, Caridad, Moshous, Despina, Blanche, Stephane, Fisher, Alain, Ruemmele, Frank M., Tissandier, Come, Ouachee-Chardin, Marie, Rieux-Laucat, Frédéric, Cavazzana, Marina, Qasim, Waseem, Lucarelli, Barbarella, Albert, Michael H., Kobayashi, Ichiro, Alonso, Laura, Diaz De Heredia, Cristina, Kanegane, Hirokazu, Lawitschka, Anita, Seo, Jong Jin, Gonzalez-Vicent, Marta, Diaz, Miguel Angel, Goyal, Rakesh Kumar, Sauer, Martin G., Yesilipek, Akif, Kim, Minsoo, Yilmaz-Demirdag, Yesim, Bhatia, Monica, Khlevner, Julie, Richmond Padilla, Erick J., Martino, Silvana, Montin, Davide, Neth, Olaf, Molinos-Quintana, Agueda, Valverde-Fernandez, Justo, Broides, Arnon, Pinsk, Vered, Ballauf, Antje, Haerynck, Filomeen, Bordon, Victoria, Dhooge, Catharina, Garcia-Lloret, Maria Laura, Bredius, Robbert G., Kałwak, Krzysztof, Haddad, Elie, Seidel, Markus Gerhard, Duckers, Gregor, Pai, Sung-Yun, Dvorak, Christopher C., Ehl, Stephan, Locatelli, Franco, Goldman, Frederick, Gennery, Andrew Richard, Cowan, Mort J., Roncarolo, Maria-Grazia, Bacchetta, Rosa

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Fast Numerical Power Loss Calculation for High-Frequency Litz Wires von Ehrlich, Stefan, Rossmanith, Hans, Sauer, Marco, Joffe, Christopher, Marz, Martin

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Systematic Review and Comparison of Publicly Available ICU Data Sets—A Decision Guide for Clinicians and Data Scientists von Sauer, Christopher M., Dam, Tariq A., Celi, Leo A., Faltys, Martin, de la Hoz, Miguel A. A., Adhikari, Lasith, Ziesemer, Kirsten A., Girbes, Armand, Thoral, Patrick J., Elbers, Paul

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Non-clinical immunological comparison of a Next-Generation 24-valent pneumococcal conjugate vaccine (VAX-24) using site-specific carrier protein conjugation to the current standard... von Fairman, Jeff, Agarwal, Paresh, Barbanel, Sandrine, Behrens, Christopher, Berges, Aym, Burky, John, Davey, Peter, Fernsten, Phil, Grainger, Chris, Guo, Sherry, Iki, Sam, Iverson, Mark, Kane, Martin, Kapoor, Neeraj, Marcq, Olivier, Migone, Thi-Sau, Sauer, Paul, Wassil, James

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Somatic mutations reveal asymmetric cellular dynamics in the early human embryo von Ju, Young Seok, Martincorena, Inigo, Gerstung, Moritz, Petljak, Mia, Alexandrov, Ludmil B., Rahbari, Raheleh, Wedge, David C., Davies, Helen R., Ramakrishna, Manasa, Fullam, Anthony, Martin, Sancha, Alder, Christopher, Patel, Nikita, Gamble, Steve, O’Meara, Sarah, Giri, Dilip D., Sauer, Torril, Pinder, Sarah E., Purdie, Colin A., Borg, Åke, Stunnenberg, Henk, van de Vijver, Marc, Tan, Benita K. T., Caldas, Carlos, Tutt, Andrew, Ueno, Naoto T., van ’t Veer, Laura J., Martens, John W. M., Sotiriou, Christos, Knappskog, Stian, Span, Paul N., Lakhani, Sunil R., Eyfjörd, Jórunn Erla, Børresen-Dale, Anne-Lise, Richardson, Andrea, Thompson, Alastair M., Viari, Alain, Hurles, Matthew E., Nik-Zainal, Serena, Campbell, Peter J., Stratton, Michael R.

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Establishing medical intelligence - leveraging FHIR to improve clinical management von Brehmer, Alexander, Sauer, Christopher M., Salazar, Jayson, Hermann, Kelsey, Kim, Moon, Keyl, Julius, Bahnsen, Fin H., Frank, Benedikt, Köhrmann, Martin, Rassaf, Tienush, Mahabadi, Amir-Abbas, Hadaschik, Boris, Darr, Christopher, Herrmann, Ken, Tan, Susanne, Buer, Jan, Brenner, Thorsten, Reinhardt, Christian, Nensa, Felix, Gertz, Michael, Egger, Jan, Kleesiek, Jens

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