On the public citation graph
Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes
0 signed · 79 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1001/jamanetworkopen.2020.17703openalex-snapshot
Comparison of International Classification of Diseases and Related Health Problems, Tenth Revision Codes With Electronic Medical Records Among Patients With Symptoms of Coronavirus Disease 2019
inferredcites →https://doi.org/10.1007/978-0-387-21606-5openalex-snapshot
The Elements of Statistical Learning
inferredcites →https://doi.org/10.1007/978-3-030-03131-2_8openalex-snapshot
Application of Machine Learning Techniques in Clinical Information Extraction
inferredcites →https://doi.org/10.1007/978-981-32-9949-8_22openalex-snapshot
Role and Challenges of Unstructured Big Data in Healthcare
inferredcites →https://doi.org/10.1007/s00415-019-09229-9openalex-snapshot
Lack of accuracy of the international classification of disease, ninth (ICD-9) codes in identifying patients with encephalitis
inferredcites →https://doi.org/10.1007/s00778-019-00552-1openalex-snapshot
Snorkel: rapid training data creation with weak supervision.
inferredcites →https://doi.org/10.1016/j.arth.2020.05.013openalex-snapshot
The Inaccuracy of ICD-10 Coding in Revision Total Hip Arthroplasty and Its Implication on Revision Data
inferredcites →https://doi.org/10.1016/j.cmpb.2019.05.024openalex-snapshot
An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes
inferredcites →https://doi.org/10.1016/j.jbi.2013.06.004openalex-snapshot
Natural language processing: State of the art and prospects for significant progress, a workshop sponsored by the National Library of Medicine
inferredcites →https://doi.org/10.1016/j.jbi.2015.09.010openalex-snapshot
A study of active learning methods for named entity recognition in clinical text
inferredcites →https://doi.org/10.1016/j.jbi.2018.10.005openalex-snapshot
Using clinical Natural Language Processing for health outcomes research: Overview and actionable suggestions for future advances
inferredcites →https://doi.org/10.1016/j.jbi.2019.103354openalex-snapshot
Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes
inferredcites →https://doi.org/10.1016/j.jegh.2011.06.003openalex-snapshot
Redefining syndromic surveillance
inferredcites →https://doi.org/10.1016/j.jpainsymman.2018.02.016openalex-snapshot
Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records
inferredcites →https://doi.org/10.1016/j.patter.2020.100019openalex-snapshot
Cross-Modal Data Programming Enables Rapid Medical Machine Learning
inferredcites →https://doi.org/10.1038/s41467-019-11012-3openalex-snapshot
Weakly supervised classification of aortic valve malformations using unlabeled cardiac MRI sequences
inferredcites →https://doi.org/10.1038/s41597-019-0055-0openalex-snapshot
BioWordVec, improving biomedical word embeddings with subword information and MeSH
inferredcites →https://doi.org/10.1038/sdata.2016.35openalex-snapshot
MIMIC-III, a freely accessible critical care database
inferredcites →https://doi.org/10.1056/nejmra1615014openalex-snapshot
Classification, Ontology, and Precision Medicine
inferredcites →https://doi.org/10.1093/bioinformatics/btz682openalex-snapshot
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
inferredcites →https://doi.org/10.1093/ckj/sfz117openalex-snapshot
Assessing the accuracy of ICD-10 coding for measuring rates of and mortality from acute kidney injury and the impact of electronic alerts: an observational cohort study
inferredcites →https://doi.org/10.1093/database/baw032openalex-snapshot
Assessing the state of the art in biomedical relation extraction: overview of the BioCreative V chemical-disease relation (CDR) task
inferredcites →https://doi.org/10.1093/jamia/ocv069openalex-snapshot
Active learning: a step towards automating medical concept extraction
inferredcites →https://doi.org/10.1093/jamia/ocy068openalex-snapshot
Opportunities and challenges in developing deep learning models using electronic health records data: a systematic review
inferredcites →https://doi.org/10.1093/jamia/ocy173openalex-snapshot
Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review
inferredcites →https://doi.org/10.1093/jamiaopen/ooy057openalex-snapshot
Weakly supervised natural language processing for assessing patient-centered outcome following prostate cancer treatment
inferredcites →https://doi.org/10.1097/nnr.0000000000000488openalex-snapshot
Identifying Symptom Information in Clinical Notes Using Natural Language Processing
inferredcites →https://doi.org/10.1109/jbhi.2017.2767063openalex-snapshot
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis
inferredcites →https://doi.org/10.1109/jbhi.2021.3062322openalex-snapshot
Limitations of Transformers on Clinical Text Classification
inferredcites →https://doi.org/10.1109/jbhi.2021.3117238openalex-snapshot
A Computational Framework to Analyze the Associations Between Symptoms and Cancer Patient Attributes Post Chemotherapy Using EHR Data
inferredcites →https://doi.org/10.1136/amiajnl-2011-000465openalex-snapshot
Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions
inferredcites →https://doi.org/10.1136/bmjqs-2018-008852openalex-snapshot
Validation of new ICD-10-based patient safety indicators for identification of in-hospital complications in surgical patients: a study of diagnostic accuracy
inferredcites →https://doi.org/10.1136/jamia.2009.001024openalex-snapshot
A systematic literature review of automated clinical coding and classification systems
inferredcites →https://doi.org/10.1136/jamia.2010.004200openalex-snapshot
Community annotation experiment for ground truth generation for the i2b2 medication challenge
inferredcites →https://doi.org/10.1177/1833358319851305openalex-snapshot
Computer-assisted clinical coding: A narrative review of the literature on its benefits, limitations, implementation and impact on clinical coding professionals
inferredcites →https://doi.org/10.1186/s12911-017-0556-8openalex-snapshot
Medical subdomain classification of clinical notes using a machine learning-based natural language processing approach
inferredcites →https://doi.org/10.1197/jamia.m1356openalex-snapshot
Implementing Syndromic Surveillance: A Practical Guide Informed by the Early Experience
inferredcites →https://doi.org/10.18653/v1/d16-1146openalex-snapshot
Lifted Rule Injection for Relation Embeddings
inferredcites →https://doi.org/10.18653/v1/p18-1098openalex-snapshot
A Neural Architecture for Automated ICD Coding
inferredcites →https://doi.org/10.18653/v1/w19-5006openalex-snapshot
Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets
inferredcites →https://doi.org/10.18653/v1/w19-5034openalex-snapshot
ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing
inferredcites →https://doi.org/10.2196/17984openalex-snapshot
Clinical Text Data in Machine Learning: Systematic Review
inferredcites →https://doi.org/10.3115/1690219.1690287openalex-snapshot
Distant supervision for relation extraction without labeled data
inferredcites →https://doi.org/10.3390/app10155262openalex-snapshot
A Comparison of Deep Learning Methods for ICD Coding of Clinical Records
inferredcites →https://doi.org/10.3390/asi4010023openalex-snapshot
A Comparative Analysis of Active Learning for Biomedical Text Mining
inferredcites →https://doi.org/10.7554/elife.58227openalex-snapshot
Augmented curation of clinical notes from a massive EHR system reveals symptoms of impending COVID-19 diagnosis
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-032-00652-3_27openalex-snapshot
High-Confidence Labelling of Pathology Reports Using LLM-Based Unanimous Ensembles with Limited Data
inferred← citeshttps://doi.org/10.1007/s11606-025-09938-0openalex-snapshot
Artificial Intelligence in Outpatient Primary Care: A Scoping Review on Applications, Challenges, and Future Directions
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.111160openalex-snapshot
A cross-modal clinical prediction system for intensive care unit patient outcome
inferred← citeshttps://doi.org/10.1016/j.smhl.2025.100540openalex-snapshot
Human knowledge-based artificial intelligence methods for skin cancer management: Accuracy and interpretability study
inferred← citeshttps://doi.org/10.1038/s41598-024-60256-7openalex-snapshot
A self-supervised framework for cross-modal search in histopathology archives using scale harmonization
inferred← citeshttps://doi.org/10.1038/s41598-025-15704-3openalex-snapshot
Integrating snapshot ensemble learning into masked autoencoders for efficient self-supervised pretraining in medical imaging
inferred← citeshttps://doi.org/10.1038/s41746-025-02111-1openalex-snapshot
Fair positive unlabeled learning for predicting undiagnosed Alzheimer’s disease in diverse electronic health records
inferred← citeshttps://doi.org/10.1080/01621459.2023.2233162openalex-snapshot
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies
inferred← citeshttps://doi.org/10.1093/jamiaopen/ooad027openalex-snapshot
Weakly supervised spatial relation extraction from radiology reports
inferred← citeshttps://doi.org/10.1101/2022.12.14.22283470openalex-snapshot
Development and validation of MedDRA Tagger: a tool for extraction and structuring medical information from clinical notes
inferred← citeshttps://doi.org/10.1109/access.2025.3603429openalex-snapshot
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach
inferred← citeshttps://doi.org/10.1109/actea66485.2025.11189906openalex-snapshot
Unsupervised Anomaly Detection in Water Distribution Networks Using One-Class SVM
inferred← citeshttps://doi.org/10.1109/bibm58861.2023.10385861openalex-snapshot
Gaussian Process-based Active Learning for Efficient Cardiovascular Disease Inference
inferred← citeshttps://doi.org/10.1109/icac60630.2023.10417152openalex-snapshot
“DiagnoMe” Mobile Application for Identifying and Predicting the Chronic Diseases
inferred← citeshttps://doi.org/10.1109/iccv51070.2023.01567openalex-snapshot
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels
inferred← citeshttps://doi.org/10.1109/imitec67386.2025.11410465openalex-snapshot
Deep Spectro-Temporal Embeddings from the M5 CNN with Spectral Clustering for Unsupervised Heartbeat Sound Clustering
inferred← citeshttps://doi.org/10.1109/iscc65549.2025.11325763openalex-snapshot
Federated and Split Learning with Frugal Labelling and Label Scarcity in Healthcare Datasets
inferred← citeshttps://doi.org/10.1109/mobilecloud62079.2024.00014openalex-snapshot
Toward Optimal Amount of Training Annotations for Waterfowl Detection and Classification
inferred← citeshttps://doi.org/10.1136/bmjpo-2026-004705openalex-snapshot
High-throughput analysis of multimodal monitoring data: the role of machine learning in early warning systems for high-risk neonates
inferred← citeshttps://doi.org/10.1145/3660647openalex-snapshot
Q-SupCon: Quantum-Enhanced Supervised Contrastive Learning Architecture within the Representation Learning Framework
inferred← citeshttps://doi.org/10.1145/3686988openalex-snapshot
Providing Context to the "Unknown": Patient and Provider Reflections on Connecting Personal Tracking, Patient-Reported Insights, and EHR Data within a Post-COVID Clinic
inferred← citeshttps://doi.org/10.1161/svin.125.001846openalex-snapshot
Natural Language Processing to Automate Cerebrovascular Event Identification in Stroke Alerts
inferred← citeshttps://doi.org/10.21203/rs.3.rs-3650733/v1openalex-snapshot
Harmonizing the Scale: An End-to-End Self-Supervised Framework for Cross-Modal Search and Retrieval in Histopathology Archives
inferred← citeshttps://doi.org/10.2196/45105openalex-snapshot
Identifying Risk Factors Associated With Lower Back Pain in Electronic Medical Record Free Text: Deep Learning Approach Using Clinical Note Annotations
inferred← citeshttps://doi.org/10.2196/49724openalex-snapshot
Task-Specific Transformer-Based Language Models in Health Care: Scoping Review
inferred← citeshttps://doi.org/10.2196/57195openalex-snapshot
Automated Identification of Postoperative Infections to Allow Prediction and Surveillance Based on Electronic Health Record Data: Scoping Review
inferred← citeshttps://doi.org/10.2196/preprints.45105openalex-snapshot
A Deep Learning Approach To Identifying Risk Factors Associated With Lower Back Pain In Electronic Medical Record Free Text (Preprint)
inferred← citeshttps://doi.org/10.3389/fdgth.2025.1497130openalex-snapshot
Synthetic4Health: generating annotated synthetic clinical letters
inferred← citeshttps://doi.org/10.3390/bioengineering12010010openalex-snapshot
Neoplasms in the Nasal Cavity Identified and Tracked with an Artificial Intelligence-Assisted Nasal Endoscopic Diagnostic System
inferred← citeshttps://doi.org/10.48084/etasr.18615openalex-snapshot
Towards the Automated Recognition of Ancient Sundanese Scripts: Groundtruth Generation at the Geusan Ulun Museum
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.