ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2017
Mining Electronic Health Records to Extract Patient-Centered Outcomes Following Prostate Cancer Treatment.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
- Using natural language processing to analyze unstructured patient-reported outcomes data derived from electronic health records for cancer populations: a systematic review.Expert review of pharmacoeconomics & outcomes research · 2024Pooled it
- Review
- NSSC: a neuro-symbolic AI system for enhancing accuracy of named entity recognition and linking from oncologic clinical notes.Medical & biological engineering & computing · 2025Article
- Natural language processing systems for extracting information from electronic health records about activities of daily living. A systematic review.JAMIA open · 2024Review
- Automated, High-Throughput Platform to Generate a High-Reliability, Comprehensive Rectal Cancer Database.JCO clinical cancer informatics · 2024Article
- Developing a Data and Analytics Platform to Enable a Breast Cancer Learning Health System at a Regional Cancer Center.JCO clinical cancer informatics · 2023Article
- Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing.JCO clinical cancer informatics · 2022Article
- Natural Language Processing to Identify Cancer Treatments With Electronic Medical Records.JCO clinical cancer informatics · 2021Article
- Phenotyping severity of patient-centered outcomes using clinical notes: A prostate cancer use case.Learning health systems · 2020Article
- An Electronic Health Record Text Mining Tool to Collect Real-World Drug Treatment Outcomes: A Validation Study in Patients With Metastatic Renal Cell Carcinoma.Clinical pharmacology and therapeutics · 2020Observational
- Leveraging Digital Data to Inform and Improve Quality Cancer Care.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020Article
- Extracting Structured Genotype Information from Free-Text HLA Reports Using a Rule-Based Approach.Journal of Korean medical science · 2020Article
- A scoping review of core outcome sets and their 'mapping' onto real-world data using prostate cancer as a case study.BMC medical research methodology · 2020Article
- Natural language processing of electronic health records is superior to billing codes to identify symptom burden in hemodialysis patients.Kidney international · 2020Article
- A frame semantic overview of NLP-based information extraction for cancer-related EHR notes.Journal of biomedical informatics · 2019Review
- Article
- Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment.JAMIA open · 2019Article
- An Automated Feature Engineering for Digital Rectal Examination Documentation using Natural Language Processing.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
The clinical, granular data in electronic health record (EHR) systems provide opportunities to improve patient care using informatics retrieval methods. However, it is well known that many methodological obstacles exist in accessing data within EHRs. In particular, clinical notes routinely stored in EHR are composed from narrative, highly unstructured and heterogeneous biomedical text. This inherent complexity hinders the ability to perform automated large-scale medical knowledge extraction tasks without the use of computational linguistics methods. The aim of this work was to develop and validate a Natural Language Processing (NLP) pipeline to detect important patient-centered outcomes (PCOs) as interpreted and documented by clinicians in their dictated notes for male patients receiving treatment for localized prostate cancer at an academic medical center.
Indexed as
Identifiers
29854154PMC5977629W2786894136What 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.