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Literature DB >> 32016531

Clinical management of sepsis can be improved by artificial intelligence: no.

José Garnacho-Montero¹, Ignacio Martín-Loeches^2,3.

Abstract

Entities: Disease

Mesh：

Year: 2020 PMID： 32016531 DOI： 10.1007/s00134-020-05947-1

Source DB: PubMed Journal: Intensive Care Med ISSN： 0342-4642 Impact factor: 17.440

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16 in total

1. Artificial intelligence in intensive care: are we there yet?

Authors: Matthieu Komorowski
Journal: Intensive Care Med Date: 2019-06-24 Impact factor: 17.440

2. A machine learning approach for predicting urine output after fluid administration.

Authors: Pei-Chen Lin; Hsu-Cheng Huang; Matthieu Komorowski; Wei-Kai Lin; Chun-Min Chang; Kuan-Ta Chen; Yu-Chuan Li; Ming-Chin Lin
Journal: Comput Methods Programs Biomed Date: 2019-05-13 Impact factor: 5.428

3. Big data and machine learning in critical care: Opportunities for collaborative research.

Authors: Antonio Núñez Reiz; Fernando Martínez Sagasti; Manuel Álvarez González; Antonio Blesa Malpica; Juan Carlos Martín Benítez; Mercedes Nieto Cabrera; Ángela Del Pino Ramírez; José Miguel Gil Perdomo; Jesús Prada Alonso; Leo Anthony Celi; Miguel Ángel Armengol de la Hoz; Rodrigo Deliberato; Kenneth Paik; Tom Pollard; Jesse Raffa; Felipe Torres; Julio Mayol; Joan Chafer; Arturo González Ferrer; Ángel Rey; Henar González Luengo; Giuseppe Fico; Ivana Lombroni; Liss Hernandez; Laura López; Beatriz Merino; María Fernanda Cabrera; María Teresa Arredondo; María Bodí; Josep Gómez; Alejandro Rodríguez; Miguel Sánchez García
Journal: Med Intensiva (Engl Ed) Date: 2018-08-02

Review 4. Big Data Analysis and Machine Learning in Intensive Care Units.

Authors: A Núñez Reiz; M A Armengol de la Hoz; M Sánchez García
Journal: Med Intensiva (Engl Ed) Date: 2018-12-24

5. Effect of a Resuscitation Strategy Targeting Peripheral Perfusion Status vs Serum Lactate Levels on 28-Day Mortality Among Patients With Septic Shock: The ANDROMEDA-SHOCK Randomized Clinical Trial.

Authors: Glenn Hernández; Gustavo A Ospina-Tascón; Lucas Petri Damiani; Elisa Estenssoro; Arnaldo Dubin; Javier Hurtado; Gilberto Friedman; Ricardo Castro; Leyla Alegría; Jean-Louis Teboul; Maurizio Cecconi; Giorgio Ferri; Manuel Jibaja; Ronald Pairumani; Paula Fernández; Diego Barahona; Vladimir Granda-Luna; Alexandre Biasi Cavalcanti; Jan Bakker; Glenn Hernández; Gustavo Ospina-Tascón; Lucas Petri Damiani; Elisa Estenssoro; Arnaldo Dubin; Javier Hurtado; Gilberto Friedman; Ricardo Castro; Leyla Alegría; Jean-Louis Teboul; Maurizio Cecconi; Maurizio Cecconi; Giorgio Ferri; Manuel Jibaja; Ronald Pairumani; Paula Fernández; Diego Barahona; Alexandre Biasi Cavalcanti; Jan Bakker; Glenn Hernández; Leyla Alegría; Giorgio Ferri; Nicolás Rodriguez; Patricia Holger; Natalia Soto; Mario Pozo; Jan Bakker; Deborah Cook; Jean-Louis Vincent; Andrew Rhodes; Bryan P Kavanagh; Phil Dellinger; Wim Rietdijk; David Carpio; Nicolás Pavéz; Elizabeth Henriquez; Sebastian Bravo; Emilio Daniel Valenzuela; Magdalena Vera; Jorge Dreyse; Vanessa Oviedo; Maria Alicia Cid; Macarena Larroulet; Edward Petruska; Claudio Sarabia; David Gallardo; Juan Eduardo Sanchez; Hugo González; José Miguel Arancibia; Alex Muñoz; Germán Ramirez; Florencia Aravena; Andrés Aquevedo; Fabián Zambrano; Milan Bozinovic; Felipe Valle; Manuel Ramirez; Victor Rossel; Pilar Muñoz; Carolina Ceballos; Christian Esveile; Cristian Carmona; Eva Candia; Daniela Mendoza; Aída Sanchez; Daniela Ponce; Daniela Ponce; Jaime Lastra; Bárbara Nahuelpán; Fabrizio Fasce; Cecilia Luengo; Nicolas Medel; Cesar Cortés; Luz Campassi; Paolo Rubatto; Nahime Horna; Mariano Furche; Juan Carlos Pendino; Lisandro Bettini; Carlos Lovesio; María Cecilia González; Jésica Rodruguez; Héctor Canales; Francisco Caminos; Cayetano Galletti; Estefanía Minoldo; Maria Jose Aramburu; Daniela Olmos; Nicolás Nin; Jordán Tenzi; Carlos Quiroga; Pablo Lacuesta; Agustín Gaudín; Richard Pais; Ana Silvestre; Germán Olivera; Gloria Rieppi; Dolores Berrutti; Marcelo Ochoa; Paul Cobos; Fernando Vintimilla; Vanessa Ramirez; Milton Tobar; Fernanda García; Fabricio Picoita; Nelson Remache; Vladimir Granda; Fernando Paredes; Eduardo Barzallo; Paul Garcés; Fausto Guerrero; Santiago Salazar; German Torres; Cristian Tana; José Calahorrano; Freddy Solis; Pedro Torres; Luís Herrera; Antonio Ornes; Verónica Peréz; Glenda Delgado; Alexei López; Eliana Espinosa; José Moreira; Blanca Salcedo; Ivonne Villacres; Jhonny Suing; Marco Lopez; Luis Gomez; Guillermo Toctaquiza; Mario Cadena Zapata; Milton Alonso Orazabal; Ruben Pardo Espejo; Jorge Jimenez; Alexander Calderón; Gustavo Paredes; José Luis Barberán; Tatiana Moya; Horacio Atehortua; Rodolfo Sabogal; Guillermo Ortiz; Antonio Lara; Fabio Sanchez; Alvaro Hernán Portilla; Humberto Dávila; Jorge Antonio Mora; Luis Eduardo Calderón; Ingrid Alvarez; Elena Escobar; Alejandro Bejarano; Luis Alfonso Bustamante; José Luis Aldana
Journal: JAMA Date: 2019-02-19 Impact factor: 56.272

6. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

Authors: Shamim Nemati; Andre Holder; Fereshteh Razmi; Matthew D Stanley; Gari D Clifford; Timothy G Buchman
Journal: Crit Care Med Date: 2018-04 Impact factor: 7.598

7. Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis.

Authors: Ryan J Delahanty; JoAnn Alvarez; Lisa M Flynn; Robert L Sherwin; Spencer S Jones
Journal: Ann Emerg Med Date: 2019-01-17 Impact factor: 5.721

8. Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

Authors: David W Shimabukuro; Christopher W Barton; Mitchell D Feldman; Samson J Mataraso; Ritankar Das
Journal: BMJ Open Respir Res Date: 2017-11-09

Clinical management of sepsis can be improved by artificial intelligence: no.

1. Artificial intelligence in intensive care: are we there yet?

2. A machine learning approach for predicting urine output after fluid administration.

3. Big data and machine learning in critical care: Opportunities for collaborative research.

Review 4. Big Data Analysis and Machine Learning in Intensive Care Units.

5. Effect of a Resuscitation Strategy Targeting Peripheral Perfusion Status vs Serum Lactate Levels on 28-Day Mortality Among Patients With Septic Shock: The ANDROMEDA-SHOCK Randomized Clinical Trial.

6. An Interpretable Machine Learning Model for Accurate Prediction of Sepsis in the ICU.

7. Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis.

8. Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

9. The Clinical Challenge of Sepsis Identification and Monitoring.

10. Machine learning in critical care: state-of-the-art and a sepsis case study.

1. Anticardiolipin Autoantibodies as Useful Biomarkers for the Prediction of Mortality in Septic Patients.

Review 2. Artificial Intelligence for Clinical Decision Support in Sepsis.