Research graph
References from MADE: leveraging informative missingness and temporal evaluation for electronic health record-based deterioration prediction in general wards. Local targets link to admitted publications; unresolved targets remain external evidence.
A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system
10.1038/s41598-024-80268-7 · 2024 · External reference
Early warning scores with and without artificial intelligence
10.1001/jamanetworkopen.2024.38986 · 2024 · External reference
Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making
10.1038/s41598-023-40661-0 · 2023 · External reference
Electronic health records to facilitate clinical research
10.1007/s00392-016-1025-6 · 2017 · External reference
Electronic health records that support health professional reflective practice: A missed opportunity in digital health
10.1007/s41666-022-00123-0 · 2022 · External reference
Prospective external validation of a deep-learning-based early-warning system for major adverse events in general wards in South Korea
10.4266/acc.000525 · 2025 · External reference
Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: A prospective observational study
10.1136/bmjhci-2024-101353 · 2025 · External reference
Early prediction of sepsis using double fusion of deep features and handcrafted features
10.1007/s10489-022-04425-z · 2023 · External reference
Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards
10.1186/s13054-023-04609-0 · 2023 · External reference
Deep learning–based early warning systems in hospitalized patients at risk of code blue events and length of stay: Retrospective real-world implementation study
10.2196/72232 · 2025 · External reference
Machine learning based forecast for the prediction of inpatient bed demand
10.1186/s12911-022-01787-9 · 2022 · External reference
Unresolved reference
External reference
Missing data matter: An empirical evaluation of the impacts of missing EHR data in comparative effectiveness research
10.1093/jamia/ocad066 · 2023 · External reference
Implicit bias in ICU electronic health record data: measurement frequencies and missing data rates of clinical variables
10.1186/s12911-025-03058-9 · 2025 · External reference
Self-supervised transformer for sparse and irregularly sampled multivariate clinical time-series
10.1145/3516367 · 2022 · External reference
Continuous patient state attention model for addressing irregularity in electronic health records
10.1186/s12911-024-02514-2 · 2024 · External reference
Imputation of missing values for electronic health record laboratory data
10.1038/s41746-021-00518-0 · 2021 · External reference
Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques
10.1016/j.artmed.2023.102587 · 2023 · External reference
Identify the most appropriate imputation method for handling missing values in clinical structured datasets: A systematic review
10.1186/s12874-024-02310-6 · 2024 · External reference
Preserving informative presence: How missing data and imputation strategies affect the performance of an AI-based early warning score
10.3390/jcm14072213 · 2025 · External reference
Motif discovery in hospital ward vital signs observation networks
10.1007/s13721-024-00490-1 · 2024 · External reference
Missing data statistics provide causal insights into data loss in diabetes health monitoring by wearable sensors
10.3390/s24051526 · 2024 · External reference
Methods to handle incomplete data
10.4103/mamcjms.mamcjms_54_20 · 2020 · External reference
Electronic medical records imputation by temporal generative adversarial network
10.1186/s13040-024-00372-2 · 2024 · External reference
Recurrent neural networks for multivariate time series with missing values
10.1038/s41598-018-24271-9 · 2018 · External reference
Brits: Bidirectional recurrent imputation for time series
2018 · External reference
The impact of feature combinations on machine learning models for in-hospital mortality prediction
10.1038/s41598-025-26611-y · 2025 · External reference
Evaluation of clinical prediction models (part 1): From development to external validation
10.1136/bmj-2023-074819 · 2024 · External reference
TRIPOD+AI statement: Updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024 · External reference
Event prediction model considering time and input error using electronic medical records in the intensive care unit: Retrospective study
10.2196/26426 · 2021 · External reference
The third international consensus definitions for sepsis and septic shock (Sepsis-3)
10.1001/jama.2016.0287 · 2016 · External reference
The value of modified early warning score (MEWS) in surgical in-patients: A prospective observational study
10.1308/003588406x130615 · 2006 · External reference
The national early warning score: From concept to NHS implementation
10.7861/clinmed.2022-news-concept · 2022 · External reference
Application of the logistic function to bio-assay
10.2307/2280041 · 1944 · External reference
Random forests
10.1023/a1010933404324 · 2001 · External reference
Unresolved reference
2016 · External reference
Long short-term memory
10.1162/neco.1997.9.8.1735 · 1997 · External reference
Attention is all you need
2017 · External reference
