Relevant bibliographies by topics / EICU Database

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'EICU Database'

Author: Grafiati
Published: 9 October 2021
Last updated: 30 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'EICU Database.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "EICU Database"

1

Jiang, Hao, Wen Xu, Wenjing Chen, et al. "Value of early critical care transthoracic echocardiography for patients undergoing mechanical ventilation: a retrospective study." BMJ Open 11, no. 10 (2021): e048646. http://dx.doi.org/10.1136/bmjopen-2021-048646.

Full text
Abstract:
ObjectivesTo evaluate whether early intensive care transthoracic echocardiography (TTE) can improve the prognosis of patients with mechanical ventilation (MV).DesignA retrospective cohort study.SettingPatients undergoing MV for more than 48 hours, based on the Medical Information Mart for Intensive Care III (MIMIC-III) database and the eICU Collaborative Research Database (eICU-CRD), were selected.Participants2931 and 6236 patients were recruited from the MIMIC-III database and the eICU database, respectively.Primary and secondary outcome measuresThe primary outcome was in-hospital mortality.
APA, Harvard, Vancouver, ISO, and other styles
2

Wang, Lu, Jieqing Chen, and Xiang Zhou. "Factors influencing sepsis associated thrombocytopenia (SAT): A multicenter retrospective cohort study." PLOS ONE 20, no. 2 (2025): e0318887. https://doi.org/10.1371/journal.pone.0318887.

Full text
Abstract:
Introduction Sepsis associated thrombocytopenia (SAT) is a common complication of sepsis. We designed this study to investigate factors influencing SAT. Methods Patients with sepsis (2984 in Peking union medical college hospital [PUMCH] database, 13165 in eICU Collaborative Research [eICU] database, 11101 in Medical Information Mart for Intensive Care IV [MIMIC-IV] database) were enrolled. Variables included basic information, comorbidities, and organ functions. Multi-variable logistic regression models and artificial neural network model were applied to determine the factors related to SAT. M
APA, Harvard, Vancouver, ISO, and other styles
3

Kim, Yun Kwan, Won-Doo Seo, Sun Jung Lee, et al. "Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study." Journal of Medical Internet Research 26 (September 17, 2024): e62890. http://dx.doi.org/10.2196/62890.

Full text
Abstract:
Background Cardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their practical application has been challenging due to a lack of generalization and validation. Additionally, the heterogeneity among patients in different ICU subtypes has not been adequately addressed. Objective This study aims to propose a clinically interpretable ensemble approach for the timely and accurate prediction of CA within 24 hours, regardless of patient heterogeneity, i
APA, Harvard, Vancouver, ISO, and other styles
4

Ziegler, Jennifer, Barret N. M. Rush, Eric R. Gottlieb, Leo Anthony Celi, and Miguel Ángel Armengol de la Hoz. "High resolution data modifies intensive care unit dialysis outcome predictions as compared with low resolution administrative data set." PLOS Digital Health 1, no. 10 (2022): e0000124. http://dx.doi.org/10.1371/journal.pdig.0000124.

Full text
Abstract:
High resolution clinical databases from electronic health records are increasingly being used in the field of health data science. Compared to traditional administrative databases and disease registries, these newer highly granular clinical datasets offer several advantages, including availability of detailed clinical information for machine learning and the ability to adjust for potential confounders in statistical models. The purpose of this study is to compare the analysis of the same clinical research question using an administrative database and an electronic health record database. The N
APA, Harvard, Vancouver, ISO, and other styles
5

Sayed, Mohammed, David Riaño, and Jesús Villar. "Predicting Duration of Mechanical Ventilation in Acute Respiratory Distress Syndrome Using Supervised Machine Learning." Journal of Clinical Medicine 10, no. 17 (2021): 3824. http://dx.doi.org/10.3390/jcm10173824.

Full text
Abstract:
Background: Acute respiratory distress syndrome (ARDS) is an intense inflammatory process of the lungs. Most ARDS patients require mechanical ventilation (MV). Few studies have investigated the prediction of MV duration over time. We aimed at characterizing the best early scenario during the first two days in the intensive care unit (ICU) to predict MV duration after ARDS onset using supervised machine learning (ML) approaches. Methods: For model description, we extracted data from the first 3 ICU days after ARDS diagnosis from patients included in the publicly available MIMIC-III database. Di
APA, Harvard, Vancouver, ISO, and other styles
6

Xu, Yuan, Sheng Chao, and Yulin Niu. "Association between the Predicted Value of APACHE IV Scores and Intensive Care Unit Mortality: A Secondary Analysis Based on EICU Dataset." Computational and Mathematical Methods in Medicine 2022 (April 6, 2022): 1–6. http://dx.doi.org/10.1155/2022/9151925.

Full text
Abstract:
Objective. The evidence regarding the relationship between Acute Physiological and Chronic Health Assessment (APACHE) IV scores and emergency intensive care unit (EICU) mortality in patients following organ transplantation remains controversial. The purpose of this study was to investigate the relationship between APACHE IV score and EICU mortality. Methods. Data from 391 American men and women admitted to the EICU after undergoing organ transplants including heart, bone marrow, liver, kidney, lung, and pancreas in the United States. We used this data to analyze the relationship between APACHE
APA, Harvard, Vancouver, ISO, and other styles
7

Hu, Tianyang, Wanjun Yao, Yu Li, and Yanan Liu. "Interaction of acute heart failure and acute kidney injury on in-hospital mortality of critically ill patients with sepsis: A retrospective observational study." PLOS ONE 18, no. 3 (2023): e0282842. http://dx.doi.org/10.1371/journal.pone.0282842.

Full text
Abstract:
Background The present study aimed to evaluate the synergistic impact of acute heart failure (AHF) and acute kidney injury (AKI) on in-hospital mortality in critically ill patients with sepsis. Methods We undertook a retrospective, observational analysis using data acquired from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database and eICU Collaborative Research Database (eICU-CRD). The effects of AKI and AHF on in-hospital mortality were examined using a Cox proportional hazards model. Additive interactions were analyzed using the relative extra risk attributable to interact
APA, Harvard, Vancouver, ISO, and other styles
8

Tang, Xiao-Wei, Wen-Sen Ren, Shu Huang, et al. "Development and validation of a nomogram for predicting in-hospital mortality of intensive care unit patients with liver cirrhosis." World Journal of Hepatology 16, no. 4 (2024): 625–39. http://dx.doi.org/10.4254/wjh.v16.i4.625.

Full text
Abstract:
BACKGROUND Liver cirrhosis patients admitted to intensive care unit (ICU) have a high mortality rate. AIM To establish and validate a nomogram for predicting in-hospital mortality of ICU patients with liver cirrhosis. METHODS We extracted demographic, etiological, vital sign, laboratory test, comorbidity, complication, treatment, and severity score data of liver cirrhosis patients from the Medical Information Mart for Intensive Care IV (MIMIC-IV) and electronic ICU (eICU) collaborative research database (eICU-CRD). Predictor selection and model building were based on the MIMIC-IV dataset. The
APA, Harvard, Vancouver, ISO, and other styles
9

Yuan, Zhen-nan, Yu-juan Xue, Hai-jun Wang, et al. "A nomogram for predicting hospital mortality of critical ill patients with sepsis and cancer: a retrospective cohort study based on MIMIC-IV and eICU-CRD." BMJ Open 13, no. 9 (2023): e072112. http://dx.doi.org/10.1136/bmjopen-2023-072112.

Full text
Abstract:
ObjectiveSepsis remains a high cause of death, particularly in immunocompromised patients with cancer. The study was to develop a model to predict hospital mortality of septic patients with cancer in intensive care unit (ICU).DesignRetrospective observational study.SettingMedical Information Mart for Intensive Care IV (MIMIC IV) and eICU Collaborative Research Database (eICU-CRD).ParticipantsA total of 3796 patients in MIMIC IV and 549 patients in eICU-CRD were included.Primary outcome measuresThe model was developed based on MIMIC IV. The internal validation and external validation were based
APA, Harvard, Vancouver, ISO, and other styles
10

Wang, Yuxing, Yuhang Tao, Ming Yuan, et al. "Relationship between the albumin-corrected anion gap and short-term prognosis among patients with cardiogenic shock: a retrospective analysis of the MIMIC-IV and eICU databases." BMJ Open 14, no. 10 (2024): e081597. http://dx.doi.org/10.1136/bmjopen-2023-081597.

Full text
Abstract:
ObjectivesWe aimed to investigate the association between the albumin-corrected anion gap (ACAG) and the prognosis of cardiogenic shock (CS).DesignA multicentre retrospective cohort study.SettingData were collected from the Medical Information Mart for Intensive Care (MIMIC-IV) and eICU Collaborative Research Database (eICU-CRD) datasets.Participants808 and 700 individuals from the MIMIC-IV and eICU-CRD, respectively, who were diagnosed with CS.Primary and secondary outcomesThe primary endpoint was short-term all-cause mortality, including intensive care unit (ICU), in-hospital and 28-day mort
APA, Harvard, Vancouver, ISO, and other styles
More sources

Dissertations / Theses on the topic "EICU Database"

1

McCullen, Jeffrey Reynolds. "Predicting the Effects of Sedative Infusion on Acute Traumatic Brain Injury Patients." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/105140.

Full text
Abstract:
Healthcare analytics has traditionally relied upon linear and logistic regression models to address clinical research questions mostly because they produce highly interpretable results [1, 2]. These results contain valuable statistics such as p-values, coefficients, and odds ratios that provide healthcare professionals with knowledge about the significance of each covariate and exposure for predicting the outcome of interest [1]. Thus, they are often favored over new deep learning models that are generally more accurate but less interpretable and scalable. However, the statistical power of lin
APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "EICU Database"

1

Andries, Coline, Paul Quindroit, Benjamin Popoff, Ikram Oudarrour, and Antoine Lamer. "Public Availability of Data Management and Analysis Scripts of Studies Conducted on Open-Access Intensive Care Databases." In Studies in Health Technology and Informatics. IOS Press, 2024. http://dx.doi.org/10.3233/shti240429.

Full text
Abstract:
Intensive care units (ICUs) provide care for critical patients at high risk of morbidity and mortality, and require continuous monitoring of clinical, biological and, imaging parameters. Collaborative ventures have enabled the emergence of large open access databases for the secondary use of Electronic Health Records (EHRs). The objective of this work was to evaluate the availability of scripts and datasets in publications based on ICU open-access databases. We included 910 original articles based on four ICU open-access databases (Amsterdam University Medical Centers Database, eICU Collaborat
APA, Harvard, Vancouver, ISO, and other styles
2

Schwinn, Johanna, Seyedmostafa Sheikhalishahi, Matthaeus Morhart, Mathias Kaspar, and Ludwig Christian Hinske. "A Federated Learning Model for the Prediction of Blood Transfusion in Intensive Care Units." In Studies in Health Technology and Informatics. IOS Press, 2025. https://doi.org/10.3233/shti250311.

Full text
Abstract:
Accurate prediction of blood transfusion requirements is crucial for patient outcomes and resource management in clinical settings. We developed a machine learning model using XGBoost to predict the need for a blood transfusion 2 hours in advance based on up to 7 hours of prior data from two large databases, MIMIC-IV and eICU-CRD. Our federated model showed promising results, with F1 scores of 0.72 and 0.66, respectively.
APA, Harvard, Vancouver, ISO, and other styles
3

Sheikhalishahi, Seyedmostafa, Johanna Schwinn, Matthaeus Morhart, Mathias Kaspar, and Ludwig Christian Hinske. "Federated Learning for Predictive Analytics in Weaning from Mechanical Ventilation." In Studies in Health Technology and Informatics. IOS Press, 2025. https://doi.org/10.3233/shti250418.

Full text
Abstract:
Mechanical ventilation is crucial for critically ill patients in ICUs, requiring accurate weaning and extubations timing for optimal outcomes. Current prediction models struggle with generalizability across datasets like MIMIC-IV and eICU-CRD. We propose a federated learning approach using XGBoost with bagging aggregation to improve weaning predictions while ensuring patient data privacy, compliant with GDPR and HIPAA. Using the OMOP Common Data Model, our method integrates machine learning techniques across three ICU databases, encompassing over 33,000 patients. Our model achieved robust perf
APA, Harvard, Vancouver, ISO, and other styles
4

"Research on Query Technology of XML Database." In International Conference on Electronics, Information and Communication Engineering (EICE 2012). ASME Press, 2012. http://dx.doi.org/10.1115/1.859971.paper120.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Lightsom, Frances L., and Alan O. Allwardt. "USGS Digital Libraries for Coastal and Marine Science." In Handbook of Research on Digital Libraries. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-879-6.ch043.

Full text
Abstract:
The U.S. Geological Survey (USGS) has developed three related digital libraries providing access to topical and georeferenced information for coastal and marine science: the Marine Realms Information Bank (MRIB) and its two offshoots, the Monterey Bay Science Digital Library and Coastal Change Hazards Digital Library. These three members of the MRIB family run on the same software and share a common database, but they employ different user interfaces targeting different audiences. This chapter reviews (1) distributed geolibraries, the conceptual foundation for MRIB, (2) the modular software of
APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "EICU Database"

1

Johnson, Alistair E. W., Tom J. Pollard, Leo A. Celi, and Roger G. Mark. "Analyzing the eICU Collaborative Research Database." In BCB '17: 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM, 2017. http://dx.doi.org/10.1145/3107411.3107494.

Full text
APA, Harvard, Vancouver, ISO, and other styles
2

Niaussat, Victor, Raphaelle Giguere, Tanya Paul, Patrick Archambault, and Alexandre Marois. "Real-Time Machine Learning for ICU Hypoxia Prediction: A Pilot Study." In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1004734.

Full text
Abstract:
Continuous and precise monitoring in the intensive care unit (ICU) are essential, particularly for patients with respiratory disorders necessitating mechanical ventilation, as they represent a critical cohort. Hypoxia can be defined as a medical condition characterized by an inadequate supply of oxygen to bodily tissues and organs, leading to an inability to meet their metabolic needs. This condition can manifest in diverse scenarios, such as high-altitude environments for example mountain climbing or in high-altitude flights. Common symptoms of hypoxia include breathing difficulties, confusio
APA, Harvard, Vancouver, ISO, and other styles
3

Janiszewski, Marek, Marcin Rytel, Piotr Lewandowski, and Hubert Romanowski. "Creating vulnerabilities and exploits database of IoT devices." In EICC 2022: European Interdisciplinary Cybersecurity Conference. ACM, 2022. http://dx.doi.org/10.1145/3528580.3532990.

Full text
APA, Harvard, Vancouver, ISO, and other styles
4

Barsha, Mithila Kundu, K. M. Azharul Hasan, and Irfat Ara. "Natural Language Interface to Database by Regular Expression Generation." In 2021 5th International Conference on Electrical Information and Communication Technology (EICT). IEEE, 2021. http://dx.doi.org/10.1109/eict54103.2021.9733592.

Full text
APA, Harvard, Vancouver, ISO, and other styles
5

Shovo, Md Shafiq Newaj, Kazi Md Rokibul Alam, Dhrubajotee Howlader, and Yasuhiko Morimoto. "A Sorting and Searching Scheme for Relational Database Using Searchable Encryption." In 2021 5th International Conference on Electrical Information and Communication Technology (EICT). IEEE, 2021. http://dx.doi.org/10.1109/eict54103.2021.9733450.

Full text
APA, Harvard, Vancouver, ISO, and other styles
You might also be interested in the extended bibliographies on the topic 'EICU Database' for particular source types:
Journal articles
We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!

To the bibliography