Machine Learning Analysis for Data Incompleteness (MADI): Analyzing the Data Completeness of Patient Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records

Author:

Gurupur Varadraj P.ORCID,Shelleh MuhammedORCID

Funder

Office of Faculty Excellence, University of Central Florida

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Landmark Facial Feature Detection to Reduce Positioning Error in Panoramic X-Rays;2024 IEEE International Conference on Electro Information Technology (eIT);2024-05-30

2. The need for innovations in healthcare systems using patient experience and advancing information technology;Journal of Integrated Design and Process Science;2023-10-17

3. THNN - A Neural Network Model for Telehealth Data Incompleteness Prediction;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

4. Analyzing the Data Completeness of Patients’ Records Using a Random Variable Approach to Predict the Incompleteness of Electronic Health Records;Applied Sciences;2022-10-24

5. PC-LSTM: Ontology-based Long Short-Term Memory State Model for Data Incompleteness Prediction;2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2022-07-11

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