Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies | Paper Citation Record

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This paper cites Werthaim, M.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Werthaim, M

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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This paper cites Goncharok, A.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Goncharok, A

Reference 3

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This paper cites Reliable Extraction of Clinical Follow-Up Instructions: A Hybrid Neural-Symbolic Pipeline.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Reliable Extraction of Clinical Follow-Up Instructions: A Hybrid Neural-Symbolic Pipeline

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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This paper cites Aperstein, A.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Aperstein, A

Reference 6

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This paper cites Do Large Language Models Need Intent? Revisiting Response Generation Strategies for Service Assistant.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Do Large Language Models Need Intent? Revisiting Response Generation Strategies for Service Assistant

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This paper cites CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks

Reference 8

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This paper cites Shapira, A.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Shapira, A

Reference 9

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Toward a Benchmark for Controllable Simulation of Imperfect Students with Large Language Models

Reference 10

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This paper cites A Controlled Synthetic Benchmark for Educational Aspect-Based Sentiment Analysis.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies A Controlled Synthetic Benchmark for Educational Aspect-Based Sentiment Analysis

Reference 11

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This paper cites Code Review Without Borders: Evaluating Synthetic vs. Real Data for Review Recommendation.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Code Review Without Borders: Evaluating Synthetic vs. Real Data for Review Recommendation

Reference 12

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This paper cites Aperstein, L.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Aperstein, L

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This paper cites Aperstein, Y.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Aperstein, Y

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This paper cites Framing, Judging, Steering: An Assessable Competency Model for Teach-ing Students to Reason With Generative AI.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Framing, Judging, Steering: An Assessable Competency Model for Teach-ing Students to Reason With Generative AI

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This paper cites From Joy to Fear: A Benchmark of Emotion Estimation in Pop Song Lyrics.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies From Joy to Fear: A Benchmark of Emotion Estimation in Pop Song Lyrics

Reference 16

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This paper cites Reading Between the Lines: Classifying Resume Seniority with Large Language Models.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Reading Between the Lines: Classifying Resume Seniority with Large Language Models

Reference 17

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This paper cites Aperstein, E.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Aperstein, E

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Generation of Synthetic Clinical Text: A Systematic Review

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies A Scoping Review of Synthetic Data Generation by Language Models in Biomedical Research and Applica- tion

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Generative AI for Synthetic Data Across Multiple Medical Modalities: A Systematic Review of Recent Developments and Challenges

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Natural Language Generation in Healthcare: A Review of Methods and Applications

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Zeng et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies NoteChat: A Dataset of Synthetic Doctor-Patient Conversations Conditioned on Clinical Notes

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies A Survey on Data Synthesis and Augmentation for Large Language Models

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies De-identification is not enough: a comparison between de-identified and synthetic clinical notes

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Kaabachi, J

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies ACI-BENCH: a Novel Ambient Clinical Intelligence Dataset for Benchmarking Automatic Visit Note Generation

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Ben Abacha et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies PriMock57: A Dataset Of Primary Care Mock Consultations

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Rujas, R

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Gormley, K

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Ritter, S

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Derczynski, E

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Scialom et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech Recognition and Natural Language Understanding of Air Traffic Control Communications

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Speech-based Slot Filling using Large Language Models

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Kao, K.-F

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Wei et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Tu et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Markel, S

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies ACE: A LLM-based Negotiation Coaching System

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Simulating Classroom Education with LLM-Empowered Agents

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Holderried et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Johri et al

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Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Jour- nal of Medical Internet Research, 2025

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Unavailable: canonical work link unavailable.

Observation dd82be5c-ab2e-48cd-88de-284a5cfe7afb · outbound

This paper cites JMIR Medical Informatics, 2026.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies JMIR Medical Informatics, 2026

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.068278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 931e32e8-5c50-402c-ad61-4f9d3d5fc4d8 · outbound

This paper cites Synthetic Patient-Physician Dialogue Generation from Clinical Notes Using LLM.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Synthetic Patient-Physician Dialogue Generation from Clinical Notes Using LLM

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.073268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 507e3bc6-8629-4232-a743-7a885508f25e · outbound

This paper cites Ben Abacha et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Ben Abacha et al

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.078280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb44dcb8-ee8b-4850-8e85-c147527c95ff · outbound

This paper cites UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?

Reference 59

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:13.845689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3a30233f-dc47-4ab7-af8c-1e9a6ae38f25 · outbound

This paper cites LLMs Can Simulate Standardized Patients via Agent Coevolution.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies LLMs Can Simulate Standardized Patients via Agent Coevolution

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.091609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5fb0573-32bf-4e7d-8bba-8f95e2a9f4c2 · outbound

This paper cites Kang et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Kang et al

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.099171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0a6b0d3-56f1-4e7e-b602-0c823ec3cc07 · outbound

This paper cites EMSDialog: Synthetic Multi-person Emergency Medical Service Dialogue Generation from Electronic Patient Care Reports via Multi-LLM Agents.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies EMSDialog: Synthetic Multi-person Emergency Medical Service Dialogue Generation from Electronic Patient Care Reports via Multi-LLM Agents

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.104487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebdbf767-6e50-49e2-b0d5-191af4cc38f4 · outbound

This paper cites BMC Emergency Medicine (arXiv:2510.21228), 2026.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies BMC Emergency Medicine (arXiv:2510.21228), 2026

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-08-07T19:41:13.537703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5dcd8e37-30aa-43cb-b6e5-f504bb80957b · outbound

This paper cites Prehospital and Disaster Medicine (PubMed 39675178), 2024.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Prehospital and Disaster Medicine (PubMed 39675178), 2024

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.114722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dfc51fc-5a86-42e9-8d32-1849fe395f60 · outbound

This paper cites Hartman et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Hartman et al

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.988075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c5a0ad68-9503-4991-8d5c-5da2e8faf9dd · outbound

This paper cites In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal Messages.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies In-Context Learning for Preserving Patient Privacy: A Framework for Synthesizing Realistic Patient Portal Messages

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.123886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f96757f7-b54f-44df-8561-291402e17b3f · outbound

This paper cites JAMIA, 32(6):1032, 2025.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies JAMIA, 32(6):1032, 2025

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.958765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 15346867-f368-4116-ab5d-9d8e127ce579 · outbound

This paper cites Yao et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Yao et al

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-08-07T19:41:13.221171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 41300fc8-2421-4071-a228-22e13f32666c · outbound

This paper cites Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!".

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Overview of the First Shared Task on Clinical Text Generation: RRG24 and "Discharge Me!"

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:13.030638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2061bb0a-aff5-4dda-a5c7-d95dd5d014d3 · outbound

This paper cites Synthetic Data Generation with LLM for Improved Depression Prediction.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Synthetic Data Generation with LLM for Improved Depression Prediction

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.145335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7db0617-9bc9-407c-aa48-3dfef759988f · outbound

This paper cites Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:12.986951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 44d2cc88-936b-4941-b2e6-da3bf6ef964a · outbound

This paper cites AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.155973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ff609b8-e6e5-4aa6-a446-1a8512493fbc · outbound

This paper cites Louie et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Louie et al

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.929578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b87b4bc1-79df-49ea-8468-3747e88c6c98 · outbound

This paper cites CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.167873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1070a7-6aaf-4b69-a540-d5d7641ac9e8 · outbound

This paper cites A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.174610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e51b053-ff4a-43b1-bc9a-949f31c6ae79 · outbound

This paper cites SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies SYNFAC-EDIT: Synthetic Imitation Edit Feedback for Factual Alignment in Clinical Summarization

Reference 76

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:12.898668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 106f235a-4ec2-4cc9-b6cf-355a118293b1 · outbound

This paper cites arXiv:2502.14921, 2025.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies arXiv:2502.14921, 2025

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.186035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76051540-3b81-48e2-a435-6e92bf791990 · outbound

This paper cites Evaluating Differentially Private Generation of Domain-Specific Text.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Evaluating Differentially Private Generation of Domain-Specific Text

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.190542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 394536fd-2d3f-483e-8bbe-20100fe8b95f · outbound

This paper cites Nayak et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Nayak et al

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.911832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 89ee9055-0ff1-40bd-8535-fd238f29cd03 · outbound

This paper cites Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation

Reference 80

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:12.627316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7fb88898-3301-430e-bede-2993007d6b19 · outbound

This paper cites Position: All Current Generative Fidelity and Diversity Metrics are Flawed.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Position: All Current Generative Fidelity and Diversity Metrics are Flawed

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.205425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed66baf3-73f2-4d32-9558-2ff35656684d · outbound

This paper cites Asgari, N.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Asgari, N

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.891981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 718cdd0c-e3a4-4c84-aa84-92a259be3f1d · outbound

This paper cites Bedrick, A.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Bedrick, A

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-08-07T19:41:12.579155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7003e803-bc42-4614-98d7-2b3f15d97d91 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 84

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.868261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f7e887ac-bea4-4ed5-bb80-c29e8ed6b2fc · outbound

This paper cites Malpractice Risks in Communication Fail- ures: 2015 Annual Benchmarking Report.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Malpractice Risks in Communication Fail- ures: 2015 Annual Benchmarking Report

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.845506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 24536ad2-f8e3-44ff-83b9-27b9ddb2398e · outbound

This paper cites Sentinel Event Data Summary (annual root-cause reports).

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Sentinel Event Data Summary (annual root-cause reports)

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.770934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 37af0d37-510e-480f-a28b-cb52e4dbeaf7 · outbound

This paper cites Iedema et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Iedema et al

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.754631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a7c2ff50-5354-4bef-ad5f-cd4e98c85598 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.735133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 08f92a8d-7e17-457c-8ac4-20075dbe515c · outbound

This paper cites Nath et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Nath et al

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.712569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6acf7eb8-ff75-4aac-b0bf-b4f766f87eaf · outbound

This paper cites Joshi, K.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Joshi, K

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.691224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27d10ab5-9803-4323-a912-6f1487814f70 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 91

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.666842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 40965995-d799-466b-b46e-422ca8f3a959 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 92

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.638761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 25b02144-2649-4cc5-99b4-9895419932be · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 93

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.620222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e8543c87-bf24-4928-b33a-be6b60ec8b2e · outbound

This paper cites An Emergency Medical Services Clinical Audit System driven by Named Entity Recognition from Deep Learning.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies An Emergency Medical Services Clinical Audit System driven by Named Entity Recognition from Deep Learning

Reference 94

Resolution: verified exact; local_arxiv, observed 2026-08-07T19:41:12.369678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a0a1ba6d-4d57-47fc-b70b-717d7e17a61f · outbound

This paper cites Wang et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Wang et al

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T19:41:15.600946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 35e66506-03ec-4cab-81a4-eb86f5cba1f2 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 96

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.573658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7b6c10f0-15e0-4fba-9c5c-f0eaf729baf9 · outbound

This paper cites an unresolved cited work.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-07T19:41:15.542305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 97bdfa92-0997-4275-a444-a32ee276534c · outbound

This paper cites MATRIX: Multi-Agent simulaTion fRamework for safe Interactions and conteXtual clinical conversational evaluation.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies MATRIX: Multi-Agent simulaTion fRamework for safe Interactions and conteXtual clinical conversational evaluation

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.304560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da53adc7-f818-424b-8621-910bb7be8891 · outbound

This paper cites AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.309786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0deb7402-7637-4294-9e6a-dbf1f047ab44 · outbound

This paper cites Qin et al.

Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies Qin et al

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T19:41:11.314817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers