Copertina

TEE4EHR: Transformer Event Encoder for Better Representation Learning in Electronic Health Records

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Karami, Hojjat, Atienza, David, Ionescu, Anisoara
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

SynEHRgy: Synthesizing Mixed-Type Structured Electronic Health Records using Decoder-Only Transformers
di: Karami, Hojjat, et al.
Pubblicazione: (2024)

TimEHR: Image-based Time Series Generation for Electronic Health Records
di: Karami, Hojjat, et al.
Pubblicazione: (2024)

FeatEHR-LLM: Leveraging Large Language Models for Feature Engineering in Electronic Health Records
di: Karami, Hojjat, et al.
Pubblicazione: (2026)

CAAT-EHR: Cross-Attentional Autoregressive Transformer for Multimodal Electronic Health Record Embeddings
di: Olaimat, Mohammad Al, et al.
Pubblicazione: (2025)

EHR2Path: Scalable Modeling of Longitudinal Patient Pathways from Multimodal Electronic Health Records
di: Pellegrini, Chantal, et al.
Pubblicazione: (2025)

Large Language Models are Powerful Electronic Health Record Encoders
di: Hegselmann, Stefan, et al.
Pubblicazione: (2025)

Learning Longitudinal Health Representations from EHR and Wearable Data
di: Zhang, Yuanyun, et al.
Pubblicazione: (2026)

FairEHR-CLP: Towards Fairness-Aware Clinical Predictions with Contrastive Learning in Multimodal Electronic Health Records
di: Wang, Yuqing, et al.
Pubblicazione: (2024)

EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records
di: Shurrab, Saeed, et al.
Pubblicazione: (2026)

Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
di: Cui, Suhan, et al.
Pubblicazione: (2024)

CDMT-EHR: A Continuous-Time Diffusion Framework for Generating Mixed-Type Time-Series Electronic Health Records
di: Liu, Shaonan, et al.
Pubblicazione: (2026)

HyMaTE: A Hybrid Mamba and Transformer Model for EHR Representation Learning
di: Mottalib, Md Mozaharul, et al.
Pubblicazione: (2025)

Self-supervised Representation Learning on Electronic Health Records with Graph Kernel Infomax
di: Yao, Hao-Ren, et al.
Pubblicazione: (2022)

MixEHR-Nest: Identifying Subphenotypes within Electronic Health Records through Hierarchical Guided-Topic Modeling
di: Wang, Ruohan, et al.
Pubblicazione: (2024)

Understanding Missingness in Time-series Electronic Health Records for Individualized Representation
di: Ghosheh, Ghadeer O., et al.
Pubblicazione: (2024)

Subpopulation-Specific Synthetic EHR for Better Mortality Prediction
di: Perets, Oriel, et al.
Pubblicazione: (2023)

Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding
di: Xiang, Xiao, et al.
Pubblicazione: (2026)

Ensemble BERT for Medication Event Classification on Electronic Health Records (EHRs)
di: Sarker, Shouvon, et al.
Pubblicazione: (2025)

The Taxonomies, Training, and Applications of Event Stream Modelling for Electronic Health Records
di: Zhu, Mingcheng, et al.
Pubblicazione: (2026)

Predictive Modeling with Temporal Graphical Representation on Electronic Health Records
di: Chen, Jiayuan, et al.
Pubblicazione: (2024)

Zero-shot Medical Event Prediction Using a Generative Pre-trained Transformer on Electronic Health Records
di: Redekop, Ekaterina, et al.
Pubblicazione: (2025)

Structure-aware Hypergraph Transformer for Diagnosis Prediction in Electronic Health Records
di: Wang, Haiyan, et al.
Pubblicazione: (2025)

Latent Factor Point Processes for Patient Representation in Electronic Health Records
di: Knight, Parker, et al.
Pubblicazione: (2025)

Contrastive Learning on Multimodal Analysis of Electronic Health Records
di: Cai, Tianxi, et al.
Pubblicazione: (2024)

MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records
di: Wang, Zekai, et al.
Pubblicazione: (2024)

BiPETE: A Bi-Positional Embedding Transformer Encoder for Risk Assessment of Alcohol and Substance Use Disorder with Electronic Health Records
di: Lee, Daniel S., et al.
Pubblicazione: (2025)

Identifying Dementia Subtypes with Electronic Health Records
di: Kumar, Sayantan, et al.
Pubblicazione: (2022)

Causal Fairness Assessment of Treatment Allocation with Electronic Health Records
di: Zhang, Linying, et al.
Pubblicazione: (2022)

Variational Encoder-Decoders for Learning Latent Representations of Physical Systems
di: Venkatasubramanian, Subashree, et al.
Pubblicazione: (2024)

WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records
di: Dong, Ruan, et al.
Pubblicazione: (2026)

Multi-task Heterogeneous Graph Learning on Electronic Health Records
di: Chan, Tsai Hor, et al.
Pubblicazione: (2024)

Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records
di: Cui, Suhan, et al.
Pubblicazione: (2024)

Understanding Transformer Encoder-Decoder Representations through Bernoulli Dropout
di: Chen, Xuanzhou
Pubblicazione: (2026)

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders
di: Kumar, Amandeep, et al.
Pubblicazione: (2026)

Guided Discrete Diffusion for Electronic Health Record Generation
di: Han, Jun, et al.
Pubblicazione: (2024)

Cross-Representation Benchmarking in Time-Series Electronic Health Records for Clinical Outcome Prediction
di: Chen, Tianyi, et al.
Pubblicazione: (2025)

Semi-supervised Clustering Through Representation Learning of Large-scale EHR Data
di: Wang, Linshanshan, et al.
Pubblicazione: (2025)

DANIEL: A Distributed and Scalable Approach for Global Representation Learning with EHR Applications
di: Wang, Zebin, et al.
Pubblicazione: (2025)

Federated Learning for Heterogeneous Electronic Health Record Systems with Cost Effective Participant Selection
di: Kim, Jiyoun, et al.
Pubblicazione: (2024)

GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records
di: Fang, Yue, et al.
Pubblicazione: (2026)