ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2020
sig2db: a Workflow for Processing Natural Language from Prescription Instructions for Clinical Data Warehouses.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Prompt Engineering of Large Language Models for Medication Dose Calculation.Clinical pharmacology and therapeutics · 2026Article
- Approaches for extracting daily dosage from free-text prescription signatures in heart failure with reduced ejection fraction: a comparative study.JAMIA open · 2025Article
- Structuring medication signeturs as a language regression task: comparison of zero- and few-shot GPT with fine-tuned models.JAMIA open · 2024Article
- Enhanced family history-based algorithms increase the identification of individuals meeting criteria for genetic testing of hereditary cancer syndromes but would not reduce disparities on their own.Journal of biomedical informatics · 2024Article
- Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review.JMIR medical informatics · 2023Review
- Extracting Semantics from Census-based Reference Data.Proceedings. IEEE International Conference on Semantic Computing · 2021Article
- Challenges and Barriers in Applying Natural Language Processing to Medical Examiner Notes from Fatal Opioid Poisoning Cases.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2020Article
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Authors and funding
3 authors.
Funding
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Abstract
We present sig2db as an open-source solution for clinical data warehouses desiring to process natural language from prescription instructions, often referred to as "sigs". In electronic prescribing, the sig is typically an unstructured text field intended to capture all requirements for medication administration. The sig captures certain fields that the structured data may lack such as days supply, time of day, or meal-time considerations. Our open-source software package facilitates the workflow needed to process sigs into a structured format usable by clinical data warehouses. Our solution focuses on extracting concepts from prescriptions in order to understand the intended semantics by leveraging known natural language processing tools. We demonstrate the utility of concept extraction from sigs and present our findings in processing 1023 unique sigs from 5.7 million unique prescriptions.
Identifiers
32477641PMC7233058What OpenQuestion holds
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.