Paper Citation Record · LEDGER

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering

As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2605.17771.

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

pith.paper-citation-record.v1
2605.17771 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T01:09:34.805401Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

17 of 17 outbound references displayed

verified exact10
verified fuzzy5
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 99be5a8b-b14d-4a57-9b25-696da00ec4dc · outbound

This paper cites Over 1 in 3 people affected by neurological conditions, the leading cause of illness and disability worldwide.”WHO News, 14 March 2024.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Over 1 in 3 people affected by neurological conditions, the leading cause of illness and disability worldwide.”WHO News, 14 March 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T01:13:19.103138Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ecbefade-e33f-42f6-89ca-a7a08236902a · outbound

This paper cites author Donoho, D.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering author Donoho, D

Reference 2

Resolution: metadata mismatch; doi, observed 2026-05-20T01:12:54.956493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5524c5f5-7b1d-454a-82b1-2789b7da0ed6 · outbound

This paper cites Compressed sens- ing MRI: A review of the clinical literature.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Compressed sens- ing MRI: A review of the clinical literature

Reference 3

Resolution: verified exact; doi, observed 2026-05-20T01:12:54.961142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eee47714-c73c-4c36-a2f8-cef0091acc12 · outbound

This paper cites 16.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering 16

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T01:13:19.106461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 96859d24-4334-46b6-9166-0d9b797cd5f8 · outbound

This paper cites Global, regional, and national burden of disor- ders affecting the nervous system, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Global, regional, and national burden of disor- ders affecting the nervous system, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T01:13:19.098474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0a113dee-f274-4321-9dba-e2852cdc6c61 · outbound

This paper cites Konar et al., ”3D Quantum-Inspired Self-Supervised Tensor Network for V olumetric Segmentation of Medical Images,”IEEE.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Konar et al., ”3D Quantum-Inspired Self-Supervised Tensor Network for V olumetric Segmentation of Medical Images,”IEEE

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.122810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 724b0ace-180d-4ae6-bf58-6771d95a00a4 · outbound

This paper cites Baraniuk and P.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Baraniuk and P

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.100602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4aafa574-6c7f-417f-972b-358a4331d2a0 · outbound

This paper cites Tensor Networks for Medical Image Classification.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Tensor Networks for Medical Image Classification

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:54.951306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08e0412c-877f-4d28-af1a-d4328f4931e3 · outbound

This paper cites Architectural Patterns for Designing Quantum Artificial Intelligence Systems.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Architectural Patterns for Designing Quantum Artificial Intelligence Systems

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.129206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93dad0d2-4605-4d8c-aca8-a3f08b8c8a14 · outbound

This paper cites Sparse Reconstruction Techniques in MRI: Methods, Applications, and Challenges to Clinical Adoption.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Sparse Reconstruction Techniques in MRI: Methods, Applications, and Challenges to Clinical Adoption

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T01:13:19.103673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cdd49107-bcd4-4083-a398-cf02fefeb718 · outbound

This paper cites Rieser, F.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Rieser, F

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T01:12:54.973038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 552cd087-563f-4f24-b503-4f5cff1d167d · outbound

This paper cites 12.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering 12

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T01:13:19.106770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67d6acb3-5244-41a1-a683-04eaed90a048 · outbound

This paper cites Advancements and Challenges in Quantum Machine Learning for Medical Image Classification: A Comprehensive Review.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Advancements and Challenges in Quantum Machine Learning for Medical Image Classification: A Comprehensive Review

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.085603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 87f59d5c-70f9-43d9-84fa-cdcba4f2d64c · outbound

This paper cites ADDIS-Graphs for online error control with application to platform trials.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering ADDIS-Graphs for online error control with application to platform trials

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.090571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0674d461-c9f7-44bd-a520-82081a991c16 · outbound

This paper cites Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy V olunteers.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy V olunteers

Reference 15

Resolution: verified exact; doi, observed 2026-05-20T01:12:54.977106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d7a81e0e-36b7-4e33-9b85-f689c5f1f2b0 · outbound

This paper cites Pre-trained deep learning models for brain MRI image classification.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Pre-trained deep learning models for brain MRI image classification

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:54.967193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cd8e5551-6008-499d-bf01-3f09941f9036 · outbound

This paper cites Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification.

Multi-Class Neurological Disorder Prediction with Tensor Network Feature Engineering Efficiency Bottlenecks of Convolutional Kolmogorov-Arnold Networks: A Comprehensive Scrutiny with ImageNet, AlexNet, LeNet and Tabular Classification

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-20T01:12:55.095630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.