Imagen de Portada

Synthetic4Health: Generating Annotated Synthetic Clinical Letters

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ren, Libo, Belkadi, Samuel, Han, Lifeng, Del-Pinto, Warren, Nenadic, Goran
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Exploration of Masked and Causal Language Modelling for Text Generation
por: Micheletti, Nicolo, et al.
Publicado: (2024)

Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language Modeling
por: Belkadi, Samuel, et al.
Publicado: (2024)

Large Language Models for Biomedical Text Simplification: Promising But Not There Yet
por: Li, Zihao, et al.
Publicado: (2024)

Investigating Large Language Models and Control Mechanisms to Improve Text Readability of Biomedical Abstracts
por: Li, Zihao, et al.
Publicado: (2023)

A Comparative Study on Automatic Coding of Medical Letters with Explainability
por: Glen, Jamie, et al.
Publicado: (2024)

CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data
por: Hong, Kung Yin, et al.
Publicado: (2024)

INSIGHTBUDDY-AI: Medication Extraction and Entity Linking using Large Language Models and Ensemble Learning
por: Romero, Pablo, et al.
Publicado: (2024)

Structured Information Matters: Explainable ICD Coding with Patient-Level Knowledge Graphs
por: Li, Mingyang, et al.
Publicado: (2025)

Neural Machine Translation of Clinical Text: An Empirical Investigation into Multilingual Pre-Trained Language Models and Transfer-Learning
por: Han, Lifeng, et al.
Publicado: (2023)

CANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation
por: Hong, Kung Yin, et al.
Publicado: (2024)

MTUncertainty: Assessing the Need for Post-editing of Machine Translation Outputs by Fine-tuning OpenAI LLMs
por: Gladkoff, Serge, et al.
Publicado: (2023)

Towards a resource for multilingual lexicons: an MT assisted and human-in-the-loop multilingual parallel corpus with multi-word expression annotation
por: Han, Lifeng, et al.
Publicado: (2020)

DeIDClinic: A Risk-Aware Pseudonymization Framework for Clinical Text De-identification and Re-identification Risk Assessment
por: Paul, Angel, et al.
Publicado: (2024)

Generation of Synthetic Clinical Text: A Systematic Review
por: Alshaikhdeeb, Basel, et al.
Publicado: (2025)

Backprompting: Leveraging Synthetic Production Data for Health Advice Guardrails
por: Cheng, Kellen Tan, et al.
Publicado: (2025)

Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes
por: Kweon, Sunjun, et al.
Publicado: (2023)

AutoLLM-CARD: Towards a Description and Landscape of Large Language Models
por: Tian, Shengwei, et al.
Publicado: (2024)

DualAlign: Generating Clinically Grounded Synthetic Data
por: Li, Rumeng, et al.
Publicado: (2025)

Retrieval-Augmented Generation Systems for Intellectual Property via Synthetic Multi-Angle Fine-tuning
por: Ren, Runtao, et al.
Publicado: (2025)

A Typology of Synthetic Datasets for Dialogue Processing in Clinical Contexts
por: Bedrick, Steven, et al.
Publicado: (2025)

MAGneT: Coordinated Multi-Agent Generation of Synthetic Multi-Turn Mental Health Counseling Sessions
por: Mandal, Aishik, et al.
Publicado: (2025)

Parameterized Synthetic Text Generation with SimpleStories
por: Finke, Lennart, et al.
Publicado: (2025)

CircuitSynth: Reliable Synthetic Data Generation
por: Cheng, Zehua, et al.
Publicado: (2026)

Synthetic Patient-Physician Dialogue Generation from Clinical Notes Using LLM
por: Das, Trisha, et al.
Publicado: (2024)

Enhancing Clinical Documentation with Synthetic Data: Leveraging Generative Models for Improved Accuracy
por: Biswas, Anjanava, et al.
Publicado: (2024)

An Empirical Study of Validating Synthetic Data for Formula Generation
por: Singh, Usneek, et al.
Publicado: (2024)

Synthetic Dialogue Dataset Generation using LLM Agents
por: Abdullin, Yelaman, et al.
Publicado: (2024)

Generating Synthetic Datasets for Few-shot Prompt Tuning
por: Guo, Xu, et al.
Publicado: (2024)

Few-shot LLM Synthetic Data with Distribution Matching
por: Ren, Jiyuan, et al.
Publicado: (2025)

SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization
por: Mishra, Prakamya, et al.
Publicado: (2024)

Synthetic Multimodal Question Generation
por: Wu, Ian, et al.
Publicado: (2024)

Synthetic bootstrapped pretraining
por: Yang, Zitong, et al.
Publicado: (2025)

MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs
por: Lu, Zimu, et al.
Publicado: (2024)

Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note Scale
por: Liu, Jinghui, et al.
Publicado: (2026)

Multi-Document Grounded Multi-Turn Synthetic Dialog Generation
por: Lee, Young-Suk, et al.
Publicado: (2024)

Optimsyn: Influence-Guided Rubrics Optimization for Synthetic Data Generation
por: Fan, Zhiting, et al.
Publicado: (2026)

Synthetic Dialogue Generation for Interactive Conversational Elicitation & Recommendation (ICER)
por: Ryu, Moonkyung, et al.
Publicado: (2025)

Synthetic Feature Augmentation Improves Generalization Performance of Language Models
por: Choudhary, Ashok, et al.
Publicado: (2025)

Generating High Quality Synthetic Data for Dutch Medical Conversations
por: Kuan, Cecilia, et al.
Publicado: (2026)

Equilibrium Dynamics and Mitigation of Gender Bias in Synthetically Generated Data
por: Kattamuri, Ashish, et al.
Publicado: (2025)