ArticleJAMIA open2022
Deep learning-based NLP data pipeline for EHR-scanned document information extraction.
Article in JAMIA open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Development of a peripheral blood transcriptomic gene signature to predict bronchopulmonary dysplasia.American journal of physiology. Lung cellular and molecular physiology · 2023Trial
- Development and validation of an algorithm to identify severe sepsis onset from electronic medical records.JAMIA open · 2026Article
- SDoH-GPT: using large language models to extract social determinants of health.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Extracting language information from clinical notes using large language models.International journal of medical informatics · 2026Article
- Enhancing Medical Diagnosis Document Analysis with Layout-Aware Multitask Models.Diagnostics (Basel, Switzerland) · 2025Article
- Cancer Diagnosis Categorization in Electronic Health Records Using Large Language Models and BioBERT: Model Performance Evaluation Study.JMIR cancer · 2025Article
- Assessment and Integration of Large Language Models for Automated Electronic Health Record Documentation in Emergency Medical Services.Journal of medical systems · 2025Article
- Experience With an Optical Character Recognition Search Application for Review of Outside Medical Records.Mayo Clinic proceedings. Digital health · 2024Article
- Age modulates the predictive value of self-reported sleepiness for all-cause mortality risk: insights from a comprehensive national database of veterans.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2024Article
- Generalizable and automated classification of TNM stage from pathology reports with external validation.Nature communications · 2024Article
- The incremental design of a machine learning framework for medical records processing.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- The Role of AI in Hospitals and Clinics: Transforming Healthcare in the 21st Century.Bioengineering (Basel, Switzerland) · 2024Review
- Extracting laboratory test information from paper-based reports.BMC medical informatics and decision making · 2023Article
- Extracting Data from the Electronic Health Record of Patients with ADHD Reveals Pediatricians' Discussions of Educational Support and Document Collection.Perspectives in health information managemen · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Scanned documents in electronic health records (EHR) have been a challenge for decades, and are expected to stay in the foreseeable future. Current approaches for processing include image preprocessing, optical character recognition (OCR), and natural language processing (NLP). However, there is limited work evaluating the interaction of image preprocessing methods, NLP models, and document layout. Materials and Methods: We evaluated 2 key indicators for sleep apnea, Apnea hypopnea index (AHI) and oxygen saturation (SaO Results: Our proposed method using ClinicalBERT reached an AUROC of 0.9743 and document accuracy of 94.76% for AHI, and an AUROC of 0.9523 and document accuracy of 91.61% for SaO Discussion: There are multiple, inter-related steps to extract meaningful information from scanned reports. While it would be infeasible to experiment with all possible option combinations, we experimented with several of the most critical steps for information extraction, including image processing and NLP. Given that scanned documents will likely be part of healthcare for years to come, it is critical to develop NLP systems to extract key information from this data. Conclusion: We demonstrated the proper use of image preprocessing and document layout could be beneficial to scanned document processing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.