Paper Citation Record · LEDGER

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules

As of 20 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2412.16758.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2412.16758 v3

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:19:44.985306Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

verified exact24
verified fuzzy5
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8627d845-2aca-4259-9d19-afa67fb06d2a · outbound

This paper cites https://www.cancer.org/content/dam/cancer.org/research/cancer-facts-and-statistics/global-cancer-fact s-and-figures/global-cancer facts-and-figures-2024.pdf.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules https://www.cancer.org/content/dam/cancer.org/research/cancer-facts-and-statistics/global-cancer-fact s-and-figures/global-cancer facts-and-figures-2024.pdf

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:19:45.722346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7dced65c-645d-43b2-be67-f856f73ba16f · outbound

This paper cites Cancer statistics, 2023.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Cancer statistics, 2023

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.848474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32d6739a-0ced-4050-bf20-2c9db269b090 · outbound

This paper cites Treatment of large stage I–II lung tumors using stereotactic body radiotherapy (SBRT): Planning considerations and early toxicity.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Treatment of large stage I–II lung tumors using stereotactic body radiotherapy (SBRT): Planning considerations and early toxicity

Reference 3

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.316159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation dcfce0c3-6667-44e4-9e4c-a9a46694ec92 · outbound

This paper cites Lung-RADS Assessment Categories 2022.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Lung-RADS Assessment Categories 2022

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:19:45.707479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 93a698b6-a8db-4195-b2b3-f031b4063e3e · outbound

This paper cites The growth feature and its diagnostic value for benign and malignant pulmonary nodules met in routine clinical practice.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules The growth feature and its diagnostic value for benign and malignant pulmonary nodules met in routine clinical practice

Reference 5

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.305931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71a203fc-a6e8-4063-be28-de99359b54ae · outbound

This paper cites Radiomics of pulmonary nodules and lung cancer.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Radiomics of pulmonary nodules and lung cancer

Reference 6

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.294790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c99a982b-c0ea-498a-af50-3c585dd34e2d · outbound

This paper cites Introduction to radiomics.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Introduction to radiomics

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.874318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbd23144-fc41-45b2-8778-8008db5b829d · outbound

This paper cites Image biomarker standardisation initiative.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Image biomarker standardisation initiative

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.878298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ebde0e1-bd0d-4d48-af65-a869d89c813a · outbound

This paper cites Computational radiomics system to decode the radiographic phenotype.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Computational radiomics system to decode the radiographic phenotype

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.882466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6fca041-5c8c-43c1-b3ce-61dab3f9ab48 · outbound

This paper cites Radiomics of CT features may be nonreproducible and redundant: influence of CT Acquisition Parameters.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Radiomics of CT features may be nonreproducible and redundant: influence of CT Acquisition Parameters

Reference 10

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.261655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f04ac1c-ff85-40f4-8155-544ef21e7ca6 · outbound

This paper cites Adjusting batch effects in microarray expression data using empirical Bayes methods.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Adjusting batch effects in microarray expression data using empirical Bayes methods

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.890342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ba2a57b-d5f0-4a66-ae30-da86ac9f5a35 · outbound

This paper cites Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

Reference 12

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.244123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 03343221-caea-44cb-a184-f7933c609894 · outbound

This paper cites Validation of a method to compensate multicenter effects affecting CT radiomics.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Validation of a method to compensate multicenter effects affecting CT radiomics

Reference 13

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.232711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8c7ca40f-84e1-4709-898c-fb1346c91406 · outbound

This paper cites an unresolved cited work.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Unresolved cited work

Reference 14

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.220564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3dbddcca-7ae2-46a1-b452-5b88869035ff · outbound

This paper cites Improved generalized ComBat methods for harmonization of radiomic features.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Improved generalized ComBat methods for harmonization of radiomic features

Reference 15

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.208475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 65a1871d-e151-4f55-9525-1195ab4a15f3 · outbound

This paper cites A guide to ComBat harmonization of Imaging Biomarkers in Multicenter Studies.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules A guide to ComBat harmonization of Imaging Biomarkers in Multicenter Studies

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.909507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 275a8377-48bb-4d67-a01a-9b79edb5f4bd · outbound

This paper cites A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules A Postreconstruction Harmonization Method for Multicenter Radiomic Studies in PET

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.912903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91ef5326-412f-41ce-a451-0ed43da11ae4 · outbound

This paper cites an unresolved cited work.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Unresolved cited work

Reference 18

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.181499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 982a08f6-38a2-4ec9-bdf6-39ddfc4d1e1e · outbound

This paper cites Development of a robust radiomic biomarker of progression-free survival in early-stage non-small cell lung cancer.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Development of a robust radiomic biomarker of progression-free survival in early-stage non-small cell lung cancer

Reference 19

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.170582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c14611bf-0148-4b95-a343-85ebff4be513 · outbound

This paper cites Radiomic phenotypes for improving early prediction of survival in stage III non-small cell lung cancer adenocarcinoma after chemoradiation.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Radiomic phenotypes for improving early prediction of survival in stage III non-small cell lung cancer adenocarcinoma after chemoradiation

Reference 20

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.159796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7f7c5eef-f3c2-4862-9800-02e77276f761 · outbound

This paper cites External validation of radiomics-based predictive models in low-dose CT screening for early lung cancer diagnosis.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules External validation of radiomics-based predictive models in low-dose CT screening for early lung cancer diagnosis

Reference 21

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.148389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 82e3a5a4-7838-4241-8fd5-6452c53d5e30 · outbound

This paper cites X-ray-computed tomography contrast agents.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules X-ray-computed tomography contrast agents

Reference 22

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.138708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d4e556be-000d-4332-90f6-82ddf069ff73 · outbound

This paper cites Pulmonary nodules: CT evaluation of enhancement with iodinated contrast material.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Pulmonary nodules: CT evaluation of enhancement with iodinated contrast material

Reference 23

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.126727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 34aec2b0-40e7-4a4e-92e4-dc6a30a3d85a · outbound

This paper cites Imaging protocols for CT chest: A recommendation.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Imaging protocols for CT chest: A recommendation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:19:45.694519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b49357a0-7837-4b88-a2b2-3cf733458ec1 · outbound

This paper cites Reproducibility of CT-based radiomic features against image resampling and perturbations for tumour and healthy kidney in renal cancer patients.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Reproducibility of CT-based radiomic features against image resampling and perturbations for tumour and healthy kidney in renal cancer patients

Reference 25

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.115158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d65d829f-a38a-4b9a-b082-9cc43fd5cc37 · outbound

This paper cites Reproducibility in radiomics: A comparison of feature extraction methods and two independent datasets.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Reproducibility in radiomics: A comparison of feature extraction methods and two independent datasets

Reference 26

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.103863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2d9aa91e-c808-4214-bcf4-d4a5c5d5691f · outbound

This paper cites Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Can radiomics features be reproducibly measured from CBCT images for patients with non-small cell lung cancer?

Reference 27

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.092054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 73ac5c6d-82d4-4c70-b5bb-40fbe5dc5ab6 · outbound

This paper cites Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Prognostic value and reproducibility of pretreatment CT texture features in stage III non-small cell lung cancer

Reference 28

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.078935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 008c265f-67a8-4ee6-bdb3-7b63a1c58bb6 · outbound

This paper cites Measuring computed tomography scanner variability of radiomics features.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Measuring computed tomography scanner variability of radiomics features

Reference 29

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.066650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 37935774-dc05-425b-b032-a8d761a68727 · outbound

This paper cites Validation of a harmonization method to correct for SUV and radiomic features variability in multi-center studies.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Validation of a harmonization method to correct for SUV and radiomic features variability in multi-center studies

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:19:45.683031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation efa1a17c-9e49-4d02-ae1c-1e8d4976f7a2 · outbound

This paper cites Radiographic Texture Reproducibility: The Impact of Different Materials, their Arrangement, and Focal Spot Size.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Radiographic Texture Reproducibility: The Impact of Different Materials, their Arrangement, and Focal Spot Size

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:19:45.672457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9316e62f-f2c6-45c8-82d1-03e6127ebdad · outbound

This paper cites Comprehensive investigation on controlling for CT imaging variabilities in radiomics studies.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Comprehensive investigation on controlling for CT imaging variabilities in radiomics studies

Reference 32

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.055290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5f4e3a71-4e3d-4c19-ad5a-4cd292b80926 · outbound

This paper cites Exploring the variability of radiomic features of lung cancer lesions on unenhanced and contrast-enhanced chest CT imaging.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Exploring the variability of radiomic features of lung cancer lesions on unenhanced and contrast-enhanced chest CT imaging

Reference 33

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.044301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation c915fd41-cd52-4832-b910-fd32d69aa5aa · outbound

This paper cites LASSO: A feature selection technique in predictive modeling for machine learning.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules LASSO: A feature selection technique in predictive modeling for machine learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T10:19:44.974302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35281c73-a443-459d-adb4-5dde40454b0d · outbound

This paper cites Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Radiomics analysis of pulmonary nodules in low-dose CT for early detection of lung cancer

Reference 35

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.031523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a2ce5d40-987e-45d1-a744-7dfbec0e3ee6 · outbound

This paper cites Correlation between radiomic features based on contrast-enhanced computed tomography images and Ki-67 proliferation index in lung cancer: A preliminary study.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Correlation between radiomic features based on contrast-enhanced computed tomography images and Ki-67 proliferation index in lung cancer: A preliminary study

Reference 36

Resolution: verified exact; raw_fallback, observed 2026-08-11T10:19:45.466470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a3ed51dc-0b21-4ced-800b-134683cd1726 · outbound

This paper cites Is tumour sphericity an important prognostic factor in patients with lung cancer? Radiotherapy and Oncology.

Training Set Augmentation and Biology-Aware Harmonization Improve Radiomic Models for Lung Cancer Prediction in Indeterminate Nodules Is tumour sphericity an important prognostic factor in patients with lung cancer? Radiotherapy and Oncology

Reference 37

Resolution: verified exact; doi, observed 2026-08-11T10:19:45.019885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

No inbound Pith citation observations are available.