Scalable and accurate deep learning with electronic health records
Explore this paper's citation graph
Summary
A representation of patients’ entire raw EHR records based on the Fast Healthcare Interoperability Resources (FHIR) format is proposed, and it is demonstrated that deep learning methods using this representation are capable of accurately predicting multiple medical events from multiple centers without site-specific data harmonization.
- Type
- article
- Published
- 2018-01-24
- Cited by
- 2,885
- References
- 121
- Access
- Open access
- OpenAlex
- https://openalex.org/W2784499877
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:7979241
Keywords
Deep learning, Scalability, Medical diagnosis, Interoperability, Raw data
References
- Predicting the Future — Big Data, Machine Learning, and Clinical Medicine
- Mining high-dimensional administrative claims data to predict early hospital readmissions
- Precision medicine--personalized, problematic, and promising.
- Procedure-based severity index for inpatients: development and validation using administrative database
- A predictive analytics approach to reducing avoidable hospital readmission
- Evaluating Discrimination of Risk Prediction Models: The C Statistic.
- An Absolute Risk Prediction Model to Determine Unplanned Cardiovascular Readmissions for Adults with Chronic Heart Failure.
- Why the C-statistic is not informative to evaluate early warning scores and what metrics to use
- Measuring the modified early warning score and the Rothman Index: Advantages of utilizing the electronic medical record in an early warning system
- Length of Stay Predictions: Improvements Through the Use of Automated Laboratory and Comorbidity Variables
- A predictive analytics approach to reducing 30-day avoidable readmissions among patients with heart failure, acute myocardial infarction, pneumonia, or COPD
- Redesigning hospital alarms for patient safety: alarmed and potentially dangerous.
- Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission
- Sustained effectiveness of a primary-team–based rapid response system
- Insights into the Problem of Alarm Fatigue with Physiologic Monitor Devices: A Comprehensive Observational Study of Consecutive Intensive Care Unit Patients
- Assessing the calibration of mortality benchmarks in critical care: The Hosmer-Lemeshow test revisited*
- Development of an automated model to predict the risk of elderly emergency medical admissions within a month following an index hospital visit: A Hong Kong experience
- Relation between troponin T concentration and mortality in patients presenting with an acute stroke: observational study
- Big Data And New Knowledge In Medicine: The Thinking, Training, And Tools Needed For A Learning Health System
- Big data in health care: using analytics to identify and manage high-risk and high-cost patients.
Cited by
- Optimal intensive care outcome prediction over time using machine learning
- Developing neural network models for early detection of cardiac arrest in emergency department.
- Fighting healthcare rocketing costs with value-based medicine: the case of stroke management
- Multitask learning and benchmarking with clinical time series data
- The Generalized Data Model for clinical research
- Embedding Complexity In the Data Representation Instead of In the Model: A Case Study Using Heterogeneous Medical Data
- Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models
- Scalable Machine Learning for Predicting At-Risk Profiles Upon Hospital Admission
- Biomedical informatics and machine learning for clinical genomics.
- Deep Representation for Patient Visits from Electronic Health Records
- A scalable discrete-time survival model for neural networks
- Designing for Democratization: Introducing Novices to Artificial Intelligence Via Maker Kits
- Preoperative predictions of in-hospital mortality using electronic medical record data
- Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
- Natural language generation for electronic health records
- Privacy, Data Mining, and Digital Profiling in Online Patient Narratives
- Opportunities in Machine Learning for Healthcare
- Towards the ‘Plateau of Productivity’: enhancing the value of machine learning in critical care
- A Treatment Engine by Predicting Next-Period Prescriptions
- Countdown Regression: Sharp and Calibrated Survival Predictions
Related papers
- Survey: Deep Learning Concepts and Techniques for Electronic Health Record
- Prediction of Accuracy in Emergency Health Records using Hybrid Machine Learning Model
- Extracting and utilizing electronic health data from Epic for research.
- Opportunities and challenges in leveraging electronic health record data in oncology.
- Using electronic health record data for clinical research: a quick guide
- OASIS role-based access control for electronic health records
- Mining electronic health record data: finding the gold nuggets
- Harnessing Big Data: A Methodological Approach to Linking Electronic Health Records with Patient-Reported Survey Data
- Deep Learning for Electronic Health Records Analytics