A text-to-tabular approach to generate synthetic patient data using LLMs | Paper Citation Record

Observation 7c74edc3-ff4b-4702-a912-7bc3b5cfc453 · outbound

This paper cites Synthetic data in health care: A narrative review,.

A text-to-tabular approach to generate synthetic patient data using LLMs Synthetic data in health care: A narrative review,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.198447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c75aa3db-471a-42ec-afba-da20f28cc48b · outbound

This paper cites Generation and evaluation of privacy preserving synthetic health data,.

A text-to-tabular approach to generate synthetic patient data using LLMs Generation and evaluation of privacy preserving synthetic health data,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.185723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1d8032b8-7607-46e9-92bc-f211ea67f386 · outbound

This paper cites Syn- thetic data generation for tabular health records: A systematic review,.

A text-to-tabular approach to generate synthetic patient data using LLMs Syn- thetic data generation for tabular health records: A systematic review,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.173555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0c2cf881-1a69-4233-8f72-bbd173ddcc9e · outbound

This paper cites Mimicking Clinical Trials with Synthetic Acute Myeloid Leukemia Patients Using Generative Artificial Intelligence,.

A text-to-tabular approach to generate synthetic patient data using LLMs Mimicking Clinical Trials with Synthetic Acute Myeloid Leukemia Patients Using Generative Artificial Intelligence,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.160946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 7b5347a1-36d2-4155-a33e-17550b4849f3 · outbound

This paper cites The Effectiveness of Data Augmentation in Image Classification using Deep Learning.

A text-to-tabular approach to generate synthetic patient data using LLMs The Effectiveness of Data Augmentation in Image Classification using Deep Learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.035342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a5faef2-60e9-4862-b843-d7430cea04bb · outbound

This paper cites Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes.

A text-to-tabular approach to generate synthetic patient data using LLMs Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.039263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aab1ba17-a35e-414a-b108-b8cc4edc5747 · outbound

This paper cites Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance,.

A text-to-tabular approach to generate synthetic patient data using LLMs Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.043807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5f6e02d-f3f5-45f4-954f-16fe4f7a9454 · outbound

This paper cites T1dCteGui: A User- Friendly Clinical Trial Enrichment Tool to Optimize T1D Prevention Studies by Leveraging AI/ML Based Synthetic Patient Population,.

A text-to-tabular approach to generate synthetic patient data using LLMs T1dCteGui: A User- Friendly Clinical Trial Enrichment Tool to Optimize T1D Prevention Studies by Leveraging AI/ML Based Synthetic Patient Population,

Reference 8

Resolution: verified exact; doi, observed 2026-08-11T20:53:46.275237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 63123ef6-3d6a-4a60-ae57-8571a4306aad · outbound

This paper cites Knowledge-based mechanistic modeling accurately predicts disease progression with gefitinib in EGFR-mutant lung adenocarcinoma,.

A text-to-tabular approach to generate synthetic patient data using LLMs Knowledge-based mechanistic modeling accurately predicts disease progression with gefitinib in EGFR-mutant lung adenocarcinoma,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.148781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c1a1ae47-b6f1-41a7-b55d-c2919ab1002d · outbound

This paper cites Digital Twin Generators for Disease Modeling.

A text-to-tabular approach to generate synthetic patient data using LLMs Digital Twin Generators for Disease Modeling

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.054415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7786f52e-0eac-4918-9fe4-332071303b65 · outbound

This paper cites Language Models are Realistic Tabular Data Generators.

A text-to-tabular approach to generate synthetic patient data using LLMs Language Models are Realistic Tabular Data Generators

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.058104Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c40917d-4319-4c6c-8ef6-3654a68059d4 · outbound

This paper cites Deep Neural Networks and Tabular Data: A Survey.

A text-to-tabular approach to generate synthetic patient data using LLMs Deep Neural Networks and Tabular Data: A Survey

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.061940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18c45436-5078-4af2-add7-b6052bcdcdff · outbound

This paper cites Using Bayesian Networks to Create Synthetic Data,.

A text-to-tabular approach to generate synthetic patient data using LLMs Using Bayesian Networks to Create Synthetic Data,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.135919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b9a4953e-44f0-43a0-9e03-6590aaf697ce · outbound

This paper cites PrivBayes: Private Data Release via Bayesian Networks,.

A text-to-tabular approach to generate synthetic patient data using LLMs PrivBayes: Private Data Release via Bayesian Networks,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.068518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af1c214e-6d32-4427-a4e8-22e6ea79ba6c · outbound

This paper cites The Synthetic Data Vault,.

A text-to-tabular approach to generate synthetic patient data using LLMs The Synthetic Data Vault,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.123275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b2acc7eb-bce7-4cbe-9ca7-cf5de5765ecb · outbound

This paper cites Copula Flows for Synthetic Data Generation.

A text-to-tabular approach to generate synthetic patient data using LLMs Copula Flows for Synthetic Data Generation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.079291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8138d1a2-45c5-4fe3-a9a1-af15955ad9ed · outbound

This paper cites Generative Adversarial Networks.

A text-to-tabular approach to generate synthetic patient data using LLMs Generative Adversarial Networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.083260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22bff48b-a398-4287-9124-8928e8259939 · outbound

This paper cites Modeling Tabular data using Conditional GAN.

A text-to-tabular approach to generate synthetic patient data using LLMs Modeling Tabular data using Conditional GAN

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.087245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 956ff68a-1228-4c9c-a05b-a2236244e100 · outbound

This paper cites CTAB-GAN: Effective Table Data Synthesizing.

A text-to-tabular approach to generate synthetic patient data using LLMs CTAB-GAN: Effective Table Data Synthesizing

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.091427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c6bf861-97e9-4be9-96db-3091c4fa1318 · outbound

This paper cites Differentially Private Generative Adversarial Network.

A text-to-tabular approach to generate synthetic patient data using LLMs Differentially Private Generative Adversarial Network

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.095348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5160a1ea-ac48-42d7-98cc-dcba049e1b3c · outbound

This paper cites PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees,.

A text-to-tabular approach to generate synthetic patient data using LLMs PATE-GAN: Generating Synthetic Data with Differential Privacy Guarantees,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.110560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 62844411-97c8-43e0-b929-bedb714d7143 · outbound

This paper cites CTAB-GAN+: Enhancing Tabular Data Synthesis.

A text-to-tabular approach to generate synthetic patient data using LLMs CTAB-GAN+: Enhancing Tabular Data Synthesis

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.103187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation afe543e1-5c0f-4f1b-982f-ee1b3bb6a399 · outbound

This paper cites Structured Denoising Diffusion Models in Discrete State- Spaces,.

A text-to-tabular approach to generate synthetic patient data using LLMs Structured Denoising Diffusion Models in Discrete State- Spaces,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.107132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e51b8c0e-ea13-4a40-a77e-f2a19d78c05c · outbound

This paper cites TabDDPM: Modelling Tabular Data with Diffusion Models.

A text-to-tabular approach to generate synthetic patient data using LLMs TabDDPM: Modelling Tabular Data with Diffusion Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.110931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0327d596-e426-4c7a-9ada-c45544b88d3f · outbound

This paper cites Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees,.

A text-to-tabular approach to generate synthetic patient data using LLMs Generating and Imputing Tabular Data via Diffusion and Flow-based Gradient-Boosted Trees,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.089815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0fc76f11-3555-40bd-b7db-7d78bc80e0d7 · outbound

This paper cites REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers.

A text-to-tabular approach to generate synthetic patient data using LLMs REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.119176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50c46d31-0a52-47f3-b3dc-d095400ba384 · outbound

This paper cites TabuLa: Harnessing Language Models for Tabular Data Synthesis.

A text-to-tabular approach to generate synthetic patient data using LLMs TabuLa: Harnessing Language Models for Tabular Data Synthesis

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.123347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92391ab5-2fda-40b0-adb2-c64a89d8a87d · outbound

This paper cites Differentially Private Tabular Data Synthesis using Large Language Models.

A text-to-tabular approach to generate synthetic patient data using LLMs Differentially Private Tabular Data Synthesis using Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.127425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b58ec5c-501f-4cf7-9ea8-661fe0b31a81 · outbound

This paper cites MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data.

A text-to-tabular approach to generate synthetic patient data using LLMs MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.131322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 913bef65-6884-4e51-abe4-b7c8ed490a9f · outbound

This paper cites Why LLMs Are Bad at Synthetic Table Generation (and what to do about it).

A text-to-tabular approach to generate synthetic patient data using LLMs Why LLMs Are Bad at Synthetic Table Generation (and what to do about it)

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.135512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6792c9e4-0df4-492d-9341-197e1b790ef9 · outbound

This paper cites Creating virtual patients using large language models: scalable, global, and low cost,.

A text-to-tabular approach to generate synthetic patient data using LLMs Creating virtual patients using large language models: scalable, global, and low cost,

Reference 31

Resolution: metadata mismatch; raw_fallback, observed 2026-08-11T20:53:46.513654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 031464d9-c336-413d-a766-64e48a49a426 · outbound

This paper cites Parkinson’s disease symptoms: The patient’s perspective,.

A text-to-tabular approach to generate synthetic patient data using LLMs Parkinson’s disease symptoms: The patient’s perspective,

Reference 32

Resolution: verified exact; doi, observed 2026-08-11T20:53:46.263882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2700fd09-1b3c-42cd-8aed-a7f67d2b2ab2 · outbound

This paper cites Alzheimer Disease,.

A text-to-tabular approach to generate synthetic patient data using LLMs Alzheimer Disease,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.079511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4a1a6dcc-6059-4ce9-9b28-ec855d37af54 · outbound

This paper cites Elephants Never Forget: Testing Language Models for Memorization of Tabular Data.

A text-to-tabular approach to generate synthetic patient data using LLMs Elephants Never Forget: Testing Language Models for Memorization of Tabular Data

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.149480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c95af0-0569-491c-b1ac-7ebafc46cf65 · outbound

This paper cites The Parkinson’s progression markers initiative (PPMI) – establishing a PD biomarker cohort,.

A text-to-tabular approach to generate synthetic patient data using LLMs The Parkinson’s progression markers initiative (PPMI) – establishing a PD biomarker cohort,

Reference 35

Resolution: verified exact; doi, observed 2026-08-11T20:53:47.068196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6f62d559-f5fc-4f42-81ea-6a27cd575b59 · outbound

This paper cites A Comparison of Accelerated and Non-accelerated MRI Scans for Brain V olume and Boundary Shift Integral Measures of V olume Change: Evidence from the ADNI Dataset,.

A text-to-tabular approach to generate synthetic patient data using LLMs A Comparison of Accelerated and Non-accelerated MRI Scans for Brain V olume and Boundary Shift Integral Measures of V olume Change: Evidence from the ADNI Dataset,

Reference 36

Resolution: verified exact; doi, observed 2026-08-11T20:53:47.056826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ac75c0c1-3544-4840-a1d7-1dcf8b98d64f · outbound

This paper cites Identification of mild cognitive impairment subtypes predicting conversion to Alzheimer’s disease using multimodal data,.

A text-to-tabular approach to generate synthetic patient data using LLMs Identification of mild cognitive impairment subtypes predicting conversion to Alzheimer’s disease using multimodal data,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.044326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3a74a82f-8a84-4b45-b8fb-3a1117bf3f29 · outbound

This paper cites [Online].

A text-to-tabular approach to generate synthetic patient data using LLMs [Online]

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.031772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 34a6afc3-92e3-4164-aab4-511438047f79 · outbound

This paper cites On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests.

A text-to-tabular approach to generate synthetic patient data using LLMs On Wasserstein Two Sample Testing and Related Families of Nonparametric Tests

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.166676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ccd4246d-0cfd-4364-81e1-d04e1a70de9d · outbound

This paper cites Divergence measures based on the Shannon entropy,.

A text-to-tabular approach to generate synthetic patient data using LLMs Divergence measures based on the Shannon entropy,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.018792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 59c521c4-005d-4307-9b1a-2df061c63296 · outbound

This paper cites Distinctive Image Features from Scale-Invariant Keypoints,.

A text-to-tabular approach to generate synthetic patient data using LLMs Distinctive Image Features from Scale-Invariant Keypoints,

Reference 41

Resolution: malformed identifier; no resolver link, observed 2026-08-11T20:53:46.174529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78809523-b9c2-471d-8ad7-af437c2c8f2e · outbound

This paper cites Gender Differences in the Prevalence of Parkinson’s Disease,.

A text-to-tabular approach to generate synthetic patient data using LLMs Gender Differences in the Prevalence of Parkinson’s Disease,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:47.006577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5a7a8863-b5c8-4ce7-aa15-b08cba9bf787 · outbound

This paper cites Quantitative Measurement of Rigidity in Parkinson’s Disease: A Systematic Review,.

A text-to-tabular approach to generate synthetic patient data using LLMs Quantitative Measurement of Rigidity in Parkinson’s Disease: A Systematic Review,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.993617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8dba7948-01b3-4d3e-990b-5742a2cc3964 · outbound

This paper cites Generation and evaluation of synthetic patient data,.

A text-to-tabular approach to generate synthetic patient data using LLMs Generation and evaluation of synthetic patient data,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.981150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 77d565a7-7561-4d67-a6a9-a17c580e30a4 · outbound

This paper cites How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models.

A text-to-tabular approach to generate synthetic patient data using LLMs How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-11T20:53:46.194320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1e5a1ce-16ed-45c8-9d64-074f5745d9cc · outbound

This paper cites Synthetic data, real errors: how (not) to publish and use synthetic data.

A text-to-tabular approach to generate synthetic patient data using LLMs Synthetic data, real errors: how (not) to publish and use synthetic data

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-08-11T20:53:46.290088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 10ad9aaf-475c-427a-a34b-efbb7ae0b558 · outbound

This paper cites For up-to-date information on the study, visit www.ppmi-info.org.

A text-to-tabular approach to generate synthetic patient data using LLMs For up-to-date information on the study, visit www.ppmi-info.org

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.967289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6965702c-5178-4c21-8cba-234091720d5a · outbound

This paper cites As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analy- sis or writing of this report.

A text-to-tabular approach to generate synthetic patient data using LLMs As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analy- sis or writing of this report

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.955340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation efb19d4a-ba18-41e2-bb47-3e2a9acf7667 · outbound

This paper cites an unresolved cited work.

A text-to-tabular approach to generate synthetic patient data using LLMs Unresolved cited work

Reference 51

Resolution: unresolved; raw_fallback, observed 2026-08-11T20:53:46.943163Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3aee2477-5279-4139-9315-a33579f17809 · outbound

This paper cites The Euclidean distance is computed for each point of the synthetic data and then averaged.

A text-to-tabular approach to generate synthetic patient data using LLMs The Euclidean distance is computed for each point of the synthetic data and then averaged

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.933268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bddb398d-9b56-451d-be7c-fa8e9049caf3 · outbound

This paper cites The evaluation process involves training the ML algorithm with synthetic data.

A text-to-tabular approach to generate synthetic patient data using LLMs The evaluation process involves training the ML algorithm with synthetic data

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T20:53:46.921556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c5d1aa07-58d3-45b9-b657-31b756712a56 · outbound

This paper cites Available: http://ieeexplore.ieee.org/document/7796926/.

A text-to-tabular approach to generate synthetic patient data using LLMs Available: http://ieeexplore.ieee.org/document/7796926/

Reference 410

Resolution: verified exact; raw_fallback, observed 2026-08-11T20:53:46.718423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 55704292-3e17-4bb7-b486-41715944e205 · outbound

This paper cites Available: https://bmcmedresmethodol.biomedcentral.

A text-to-tabular approach to generate synthetic patient data using LLMs Available: https://bmcmedresmethodol.biomedcentral

Reference 2020

Resolution: verified exact; doi, observed 2026-08-11T20:53:46.251676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers