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Multimodal Learning for Cardiovascular Risk Prediction using EHR Data

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-00934-2_62openalex-snapshot

TextRay: Mining Clinical Reports to Gain a Broad Understanding of Chest X-Rays

inferredcites →https://doi.org/10.1007/s00330-020-06721-zopenalex-snapshot

Identification of patients with carotid stenosis using natural language processing

inferredcites →https://doi.org/10.1007/s10278-011-9411-0openalex-snapshot

Automatically Correlating Clinical Findings and Body Locations in Radiology Reports Using MedLEE

inferredcites →https://doi.org/10.1007/s10844-020-00605-wopenalex-snapshot

ETM: Enrichment by topic modeling for automated clinical sentence classification to detect patients’ disease history

inferredcites →https://doi.org/10.1016/j.artmed.2020.101878openalex-snapshot

Deep learning in generating radiology reports: A survey

inferredcites →https://doi.org/10.1016/j.jbi.2011.03.011openalex-snapshot

Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm

inferredcites →https://doi.org/10.1016/j.jbi.2015.08.002openalex-snapshot

Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes

inferredcites →https://doi.org/10.1016/j.jbi.2017.11.011openalex-snapshot

Clinical information extraction applications: A literature review

inferredcites →https://doi.org/10.1016/j.media.2020.101797openalex-snapshot

PadChest: A large chest x-ray image dataset with multi-label annotated reports

inferredcites →https://doi.org/10.1023/a:1007621514757openalex-snapshot

Second Manifestations of ARTerial disease (SMART) study: Rationale and design

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/jamia/ocv115openalex-snapshot

Data integration of structured and unstructured sources for assigning clinical codes to patient stays

inferredcites →https://doi.org/10.1093/jamia/ocz085openalex-snapshot

ML-Net: multi-label classification of biomedical texts with deep neural networks

inferredcites →https://doi.org/10.1109/78.650093openalex-snapshot

Bidirectional recurrent neural networks

inferredcites →https://doi.org/10.1109/icdm.2008.150openalex-snapshot

Text Mining in Radiology Reports

inferredcites →https://doi.org/10.1109/ijcnn.2017.7966408openalex-snapshot

Classification of radiology reports using neural attention models

inferredcites →https://doi.org/10.1136/jamia.1994.95236146openalex-snapshot

A General Natural-language Text Processor for Clinical Radiology

inferredcites →https://doi.org/10.1136/jamia.2009.001560openalex-snapshot

Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications

inferredcites →https://doi.org/10.1145/2975167.2975176openalex-snapshot

Text Classification with Topic-based Word Embedding and Convolutional Neural Networks

inferredcites →https://doi.org/10.1148/radiographics.21.1.g01ja18237openalex-snapshot

Automatic Structuring of Radiology Free-Text Reports

inferredcites →https://doi.org/10.1148/radiol.16142770openalex-snapshot

Natural Language Processing in Radiology: A Systematic Review

inferredcites →https://doi.org/10.1148/radiol.2017171115openalex-snapshot

Deep Learning to Classify Radiology Free-Text Reports

inferredcites →https://doi.org/10.1148/radiol.2018171093openalex-snapshot

Natural Language–based Machine Learning Models for the Annotation of Clinical Radiology Reports

inferredcites →https://doi.org/10.1148/radiol.2241011118openalex-snapshot

Use of Natural Language Processing to Translate Clinical Information from a Database of 889,921 Chest Radiographic Reports

inferredcites →https://doi.org/10.1186/s13326-019-0211-7openalex-snapshot

Text mining brain imaging reports

inferredcites →https://doi.org/10.1371/journal.pone.0030412openalex-snapshot

Extracting Diagnoses and Investigation Results from Unstructured Text in Electronic Health Records by Semi-Supervised Machine Learning

inferredcites →https://doi.org/10.1371/journal.pone.0229963openalex-snapshot

Supervised and unsupervised language modelling in Chest X-Ray radiological reports

inferredcites →https://doi.org/10.18637/jss.v045.i03openalex-snapshot

mice: Multivariate Imputation by Chained Equations inR

inferredcites →https://doi.org/10.18653/v1/n16-1056openalex-snapshot

Bidirectional RNN for Medical Event Detection in Electronic Health Records

inferredcites →https://doi.org/10.18653/v1/w16-6103openalex-snapshot

Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks

inferredcites →https://doi.org/10.2196/12239openalex-snapshot

Natural Language Processing of Clinical Notes on Chronic Diseases: Systematic Review

inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot

Glove: Global Vectors for Word Representation

inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot

Efficient Estimation of Word Representations in Vector Space

inferredcites →https://doi.org/10.48550/arxiv.1310.4546openalex-snapshot

Distributed Representations of Words and Phrases and their Compositionality

inferredcites →https://doi.org/10.48550/arxiv.1808.04928openalex-snapshot

Deep EHR: Chronic Disease Prediction Using Medical Notes

inferredcites →https://doi.org/10.48550/arxiv.1810.13348openalex-snapshot

Multimodal Machine Learning for Automated ICD Coding

inferredcites →https://doi.org/10.48550/arxiv.1811.12276openalex-snapshot

Improving Hospital Mortality Prediction with Medical Named Entities and Multimodal Learning

inferredcites →https://doi.org/10.48550/arxiv.1904.05342openalex-snapshot

ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission

inferredcites →https://doi.org/10.48550/arxiv.2002.06588openalex-snapshot

Automated Labelling using an Attention model for Radiology reports of MRI scans (ALARM)

inferredcites →https://doi.org/10.48550/arxiv.2004.09167openalex-snapshot

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT

inferredcites →https://doi.org/10.5220/0009372600002513openalex-snapshot

Automatic ICD-10 Classification of Diseases from Dutch Discharge Letters

inferredcites →https://doi.org/10.5281/zenodo.3604680openalex-snapshot

vankesteren/firatheme: firatheme version 0.2.1

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Natural Language Processing (NLP) Based Innovations for Smart Healthcare Applications in Healthcare 4.0

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Healthcare Informatics: Transforming Patient Care with Multimodal Machine Learning

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Machine Learning for Multimodal Electronic Health Records-Based Research: Challenges and Perspectives

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Role of Artificial Intelligence in the Diagnosis and Therapy of Gynecological Disorders: Opportunities and Challenges

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What are you looking at? Modality contribution in multimodal medical deep learning

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inferred← citeshttps://doi.org/10.1016/j.cmpb.2021.106395openalex-snapshot

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Enhancing clinical trial outcome prediction with artificial intelligence: a systematic review

inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117006openalex-snapshot

An overview of deep learning methods for multimodal medical data mining

inferred← citeshttps://doi.org/10.1016/j.inffus.2026.104573openalex-snapshot

Advancing ICU decision making through multimodal data fusion in predicting cardiovascular disorders

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RETRACTED ARTICLE: Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats

inferred← citeshttps://doi.org/10.1038/s41467-025-55879-xopenalex-snapshot

Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats

inferred← citeshttps://doi.org/10.1038/s41746-022-00689-4openalex-snapshot

Integrated multimodal artificial intelligence framework for healthcare applications

inferred← citeshttps://doi.org/10.1101/2023.03.10.23286918openalex-snapshot

Medical history predicts phenome-wide disease onset and enables the rapid response to emerging health threats

inferred← citeshttps://doi.org/10.1109/acoit66109.2025.11437036openalex-snapshot

AI-Driven Horizons: A Wide-Ranging Review of Deep Learning Approaches for Heart Disease Risk Prediction

inferred← citeshttps://doi.org/10.1109/gseact68539.2026.11620414openalex-snapshot

Early Detection and Progression Prediction of Kidney Diseases: A Comprehensive Review

inferred← citeshttps://doi.org/10.1109/icaiihi57871.2023.10489150openalex-snapshot

Prediction of Stroke Risk with LSTM Networks and Patient Health Records

inferred← citeshttps://doi.org/10.1109/qpain66474.2025.11171821openalex-snapshot

Cardiopredictor: A Real-Time Non-Invasive and Cuffless Cardiovascular Disease Prediction System Using 10 Fold Cross Validation on the Framingham Dataset

inferred← citeshttps://doi.org/10.21203/rs.3.rs-10147466/v1openalex-snapshot

BioPretext: A Multimodal Self-Supervised Learning Framework for Orthopedic Feature Extraction via Cross-Modal Signal Alignment and Dynamic Fusion

inferred← citeshttps://doi.org/10.2139/ssrn.4855246openalex-snapshot

Multimodal Ai for the Automatic Screening of Cardiovascular Diseases Based on Nocturnal Physiological Signals

inferred← citeshttps://doi.org/10.33540/531openalex-snapshot

Text Mining in Healthcare: Bringing Structure to Electronic Health Records

inferred← citeshttps://doi.org/10.3390/diagnostics12102536openalex-snapshot

Pneumonia and Pulmonary Thromboembolism Classification Using Electronic Health Records

inferred← citeshttps://doi.org/10.3390/info16010054openalex-snapshot

Multi-Modal Fusion of Routine Care Electronic Health Records (EHR): A Scoping Review

inferred← citeshttps://doi.org/10.3390/jcm15156053openalex-snapshot

Artificial Intelligence in Cardiovascular Risk Prediction: An Up-to-Date Narrative Review on the Emerging Role of Lipid Profile-Based Models

inferred← citeshttps://doi.org/10.3390/s23146571openalex-snapshot

Improving Diagnostics with Deep Forest Applied to Electronic Health Records

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