Paper Citation Record · LEDGER

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor

As of 11 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2607.26834.

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

pith.paper-citation-record.v1
2607.26834 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T19:43:21.613167Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

30 of 30 outbound references displayed

verified exact0
verified fuzzy0
unresolved28
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External citation measurements

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Outbound references

Observation 47968743-0d4d-479d-9325-a60e1ffc784b · outbound

This paper cites An integrative model of cellular states, plasticity, and g enetics for glioblastoma,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor An integrative model of cellular states, plasticity, and g enetics for glioblastoma,

Reference 1

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Observation 35b55603-78e0-400b-ad0b-fb81aa9fbf20 · outbound

This paper cites A nationwide population-based study on overall survival aft er meningioma surgery,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor A nationwide population-based study on overall survival aft er meningioma surgery,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.378285Z

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Observation 23cae565-166f-4004-a2df-909744736d96 · outbound

This paper cites Radiotherapy plus concomitant and adjuvant temozo lomide for glioblastoma,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Radiotherapy plus concomitant and adjuvant temozo lomide for glioblastoma,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.404739Z

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Observation db071aa3-b909-4a96-9580-5e4bedeb1330 · outbound

This paper cites Artiﬁci al intelligence-based biomarkers for treatment decisions in oncology,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Artiﬁci al intelligence-based biomarkers for treatment decisions in oncology,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.431451Z

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Observation 2c8d41b7-ca8b-4a64-8d2b-3e84afe2abb9 · outbound

This paper cites Radiomics in medical imaging—“how-to.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Radiomics in medical imaging—“how-to

Reference 5

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Observation 5e7ce747-b274-4301-9d27-cd0ef4057b32 · outbound

This paper cites Glioblastoma overall survival prediction with vision transformers,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Glioblastoma overall survival prediction with vision transformers,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.481235Z

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Observation 3d39ff28-efcd-40d8-874a-bdd29ac92b99 · outbound

This paper cites Lightweight ensemble vision transformer fra mework for non-invasive survival prediction in glioblastoma,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Lightweight ensemble vision transformer fra mework for non-invasive survival prediction in glioblastoma,

Reference 7

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Observation 7375f0af-57b7-4aab-b4a0-1c7ec39003d6 · outbound

This paper cites Radiomics: Extracting more information fr om medical images using advanced feature analysis,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Radiomics: Extracting more information fr om medical images using advanced feature analysis,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.500090Z

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Observation b5e63e16-9d86-4c30-88de-a21b4f43e62e · outbound

This paper cites Radiomic proﬁling of glioblastoma: Identifying an imagin g predictor of patient survival with improved performance over establi shed clinical and radiologic risk models,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Radiomic proﬁling of glioblastoma: Identifying an imagin g predictor of patient survival with improved performance over establi shed clinical and radiologic risk models,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.504682Z

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Observation 1715ef42-5667-4a59-9297-e5431f3020e7 · outbound

This paper cites Investigating a quantitative radiomics approach for brain tumor classiﬁca tion,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Investigating a quantitative radiomics approach for brain tumor classiﬁca tion,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.509854Z

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Observation 12140e6d-3178-4a64-b767-cb1ccf7aa160 · outbound

This paper cites Le- sion location implemented magnetic resonance imaging radi omics for predicting IDH and TERT promoter mutations in grade II/III g liomas,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Le- sion location implemented magnetic resonance imaging radi omics for predicting IDH and TERT promoter mutations in grade II/III g liomas,

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-07-30T19:43:21.515024Z

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Observation 7f4d95ee-3af0-4e6f-bbf3-133a801037c2 · outbound

This paper cites AI and machine learning in medical imaging: Key points from development to translation,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor AI and machine learning in medical imaging: Key points from development to translation,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.519971Z

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Observation d411ed50-a602-4d2e-82f6-f63670b491cd · outbound

This paper cites The widen ing gap between radiomics research and clinical translation: Reth inking current practices and shared responsibilities,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor The widen ing gap between radiomics research and clinical translation: Reth inking current practices and shared responsibilities,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.526228Z

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Observation f75e82fa-957e-4ad3-8aad-263a594c8a6f · outbound

This paper cites Data v isualization support for interdisciplinary team treatment planning in c linical oncol- ogy: Scoping review,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Data v isualization support for interdisciplinary team treatment planning in c linical oncol- ogy: Scoping review,

Reference 14

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Source-reported events for the cited work

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Observation 1c0fb7c3-9aee-477a-8161-d074153aa88c · outbound

This paper cites State-of-the -art dashboards on clinical indicator data to support reﬂection on practice : Scoping review,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor State-of-the -art dashboards on clinical indicator data to support reﬂection on practice : Scoping review,

Reference 15

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Observation 9026ea7c-1597-4146-b57d-4854b07dc9c7 · outbound

This paper cites Deve lopment, implementation, and evaluation methods for dashboards in h ealth care: Scoping review,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Deve lopment, implementation, and evaluation methods for dashboards in h ealth care: Scoping review,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.541740Z

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Observation 1f2b4d2d-0403-4c11-9803-fa1241048431 · outbound

This paper cites De velopment of an electronic health record-integrated patient-report ed outcome-based shared decision-making dashboard in oncology,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor De velopment of an electronic health record-integrated patient-report ed outcome-based shared decision-making dashboard in oncology,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.546678Z

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Observation 7b7af0c8-9489-45fb-97d1-6a2cf5a7cb19 · outbound

This paper cites Perry, V.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Perry, V

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.551171Z

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Observation 89c9d781-bbe6-4dfc-907c-9941c2d6c366 · outbound

This paper cites Empowering personalized oncology: Evolution of digital support and vi sualization tools for molecular tumor boards,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Empowering personalized oncology: Evolution of digital support and vi sualization tools for molecular tumor boards,

Reference 19

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Observation 17b38d9a-31d0-4dee-94c8-11cb6e31bd58 · outbound

This paper cites MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor MONAI Label: A framework for AI-assisted interactive labeling of 3D medical images,

Reference 20

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Observation 4b6fed64-0daf-457a-babd-a64d539d4bb6 · outbound

This paper cites 3D Slicer as an image computing platform for the Quantitative Imaging Network,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor 3D Slicer as an image computing platform for the Quantitative Imaging Network,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.565856Z

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Observation 1f65f022-4dae-4731-9845-b8814682cf7a · outbound

This paper cites Brain tumor detection and segmentation: Interactive fram ework with a visual interface and feedback facility for dynamically imp roved accuracy and trust,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Brain tumor detection and segmentation: Interactive fram ework with a visual interface and feedback facility for dynamically imp roved accuracy and trust,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.573377Z

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Observation a553edc6-7d0c-408e-831c-c1ed803ee75b · outbound

This paper cites A pipeline for the implementation and visualization of expla inable machine learning for medical imaging using radiomics features,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor A pipeline for the implementation and visualization of expla inable machine learning for medical imaging using radiomics features,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.578793Z

Source-reported events for the cited work

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Observation bfb2e465-425c-4fe5-80d8-a65822d074b8 · outbound

This paper cites 3D Slicer as a tool for interac tive brain tumor segmentation,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor 3D Slicer as a tool for interac tive brain tumor segmentation,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.583371Z

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Observation d9840a0e-ebae-4f62-8783-d810a2971ff6 · outbound

This paper cites AI-assisted seg mentation tool for brain tumor MR image analysis,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor AI-assisted seg mentation tool for brain tumor MR image analysis,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.588169Z

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Observation 56ca7b1d-b087-4a65-80aa-2c836de60863 · outbound

This paper cites T he multimodal brain tumor image segmentation benchmark (BRA T S),.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor T he multimodal brain tumor image segmentation benchmark (BRA T S),

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.592897Z

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Observation 4a0c11c2-ac4d-4063-8493-4d4fbbd8af30 · outbound

This paper cites Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentati on labels and radiomic features,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentati on labels and radiomic features,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.597426Z

Source-reported events for the cited work

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Observation 62c9f188-1742-42bd-b8e8-80b8b637e11b · outbound

This paper cites Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.602531Z

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Observation 83fd168b-2d30-442d-9ed0-80424b892635 · outbound

This paper cites Developing an au dit and feedback dashboard for family physicians: User-center ed design process,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Developing an au dit and feedback dashboard for family physicians: User-center ed design process,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.608567Z

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Observation 1d43de70-f103-4dfb-884e-d4c783fa8d8d · outbound

This paper cites Improving br ain tumor classiﬁcation efﬁcacy through the application of feature s election and ensemble classiﬁers,.

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor Improving br ain tumor classiﬁcation efﬁcacy through the application of feature s election and ensemble classiﬁers,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-30T19:43:21.613167Z

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Pith citing papers

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