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Paper Citation Record · LEDGER

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2506.14970.

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

pith.paper-citation-record.v1
2506.14970 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:13:38.761261Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:45:24.787032Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T00:45:28.070677Z

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fea228b9-0995-4f00-8fc9-0f01d429e57a · outbound

This paper cites The emerging evidence of the parkinson pandemic,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification The emerging evidence of the parkinson pandemic,

Reference 1

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Observation 9c627fd2-50fd-486b-a12a-56d6c1ce21af · outbound

This paper cites Mds clinical diagnostic criteria for parkinson’s disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Mds clinical diagnostic criteria for parkinson’s disease,

Reference 2

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Observation 54833d08-323f-430c-83d1-a6a1c82d8517 · outbound

This paper cites Preclinical biomarkers of parkinson disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Preclinical biomarkers of parkinson disease,

Reference 3

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Observation d79f41d2-441f-4a8c-ae23-f1528bb6c00b · outbound

This paper cites Clinical utility of synuclein skin biopsy in the diagnosis and evaluation of synucle- inopathies,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Clinical utility of synuclein skin biopsy in the diagnosis and evaluation of synucle- inopathies,

Reference 4

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Observation e879590a-fb7f-446c-825a-9b8978fe8dc2 · outbound

This paper cites Factors associated with phenoconversion of idiopathic rapid eye movement sleep behavior disorder: a prospective study,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Factors associated with phenoconversion of idiopathic rapid eye movement sleep behavior disorder: a prospective study,

Reference 5

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Observation 577b8345-d574-4f4d-9adf-3edaa8f595e2 · outbound

This paper cites Evolution patterns of probable rem sleep behavior disorder predicts parkinson’s disease progression,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Evolution patterns of probable rem sleep behavior disorder predicts parkinson’s disease progression,

Reference 6

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Observation a5041aaa-4959-44f3-b382-8b8f8a9ee4c2 · outbound

This paper cites Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson’s disease - npj Parkinson’s Disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Mining imaging and clinical data with machine learning approaches for the diagnosis and early detection of Parkinson’s disease - npj Parkinson’s Disease,

Reference 7

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Source-reported events for the cited work

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Observation b2421bbd-fb88-4779-ad06-1267ca051d34 · outbound

This paper cites Utility of multi-modal mri for differentiating of parkinson’s disease and progressive supranuclear palsy using machine learning,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Utility of multi-modal mri for differentiating of parkinson’s disease and progressive supranuclear palsy using machine learning,

Reference 8

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Observation 4df717ae-300a-4bb6-9f51-181aec09828f · outbound

This paper cites Machine learning classification of functional neurological disorder using structural brain mri features,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Machine learning classification of functional neurological disorder using structural brain mri features,

Reference 9

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Observation 00580bc1-9749-4be3-8a32-73b8bc633412 · outbound

This paper cites Machine learning-based framework for differential diagnosis between vascular dementia and alzheimer’s disease using structural mri features,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Machine learning-based framework for differential diagnosis between vascular dementia and alzheimer’s disease using structural mri features,

Reference 10

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Observation 83ad576f-9981-485b-ba39-b9f9d122405a · outbound

This paper cites Machine-learning classi- fication using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Machine-learning classi- fication using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis,

Reference 11

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Observation 007e417f-7086-4e03-84e8-d680d98c0e79 · outbound

This paper cites High accuracy diagnosis for mri imaging of alzheimer’s disease using xgboost,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification High accuracy diagnosis for mri imaging of alzheimer’s disease using xgboost,

Reference 12

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Source-reported events for the cited work

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Observation bd3f2245-6096-429a-a965-269c786195b7 · outbound

This paper cites Multi-channel deep model for classification of alzheimer’s disease using transfer learning,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Multi-channel deep model for classification of alzheimer’s disease using transfer learning,

Reference 13

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Source-reported events for the cited work

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Observation e3987f61-d121-495f-90df-bd96dd55c85a · outbound

This paper cites Multimodal attention-based deep learning for alzheimer’s disease diagnosis,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Multimodal attention-based deep learning for alzheimer’s disease diagnosis,

Reference 14

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Observation 2cc30f7d-53fc-4d73-bf54-0b2ec25193b2 · outbound

This paper cites Multimodal transformer network for incomplete image generation and diagnosis of alzheimer’s disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Multimodal transformer network for incomplete image generation and diagnosis of alzheimer’s disease,

Reference 15

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Observation eed53236-56ed-4d78-b789-52dc2dac905e · outbound

This paper cites A survey on mixture of experts,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification A survey on mixture of experts,

Reference 16

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Observation 410ba68d-a6bb-4534-9f85-a93a0880be58 · outbound

This paper cites Considering REM sleep behavior disorder in the management of parkinson’s disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Considering REM sleep behavior disorder in the management of parkinson’s disease,

Reference 17

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Source-reported events for the cited work

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Observation 9431ce38-a5e6-450d-b41a-bf1a1f94ac80 · outbound

This paper cites A neurologist’s guide to rem sleep behavior disorder,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification A neurologist’s guide to rem sleep behavior disorder,

Reference 18

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Observation 29f0f708-a819-454b-a0da-00510ce50b8a · outbound

This paper cites Rem sleep and neurodegeneration,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Rem sleep and neurodegeneration,

Reference 19

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Observation 85608b58-576f-4678-8c27-902866493f3f · outbound

This paper cites Interhemispheric functional and structural disconnection in alzheimer’s disease: A combined resting-state fmri and dti study,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Interhemispheric functional and structural disconnection in alzheimer’s disease: A combined resting-state fmri and dti study,

Reference 20

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Source-reported events for the cited work

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Observation 11940a07-6513-440e-9d6d-13f82d42f196 · outbound

This paper cites T1ρand T2ρMRI in the evaluation of parkinson’s disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification T1ρand T2ρMRI in the evaluation of parkinson’s disease,

Reference 21

Resolution
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Observation 1f93aa66-c292-4e4b-8d2c-e07eab4ff200 · outbound

This paper cites Diffusion magnetic resonance imaging-based biomarkers for neurodegenerative diseases,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Diffusion magnetic resonance imaging-based biomarkers for neurodegenerative diseases,

Reference 22

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Observation ad49b4d6-bd2b-47e4-89ba-fc0d5fbb99a4 · outbound

This paper cites Multi-modal brain MRI in subjects with PD and iRBD,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Multi-modal brain MRI in subjects with PD and iRBD,

Reference 23

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Observation 9ba3b60b-6397-4427-8c47-1a743f7e8d8d · outbound

This paper cites Neuroimaging in the early diagnosis of neurodegener- ative disease,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Neuroimaging in the early diagnosis of neurodegener- ative disease,

Reference 24

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Source-reported events for the cited work

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Observation a969aeab-c5f3-4d79-be3f-331cb5916807 · outbound

This paper cites Early prediction of alzheimer’s disease and related dementias using real-world electronic health records,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Early prediction of alzheimer’s disease and related dementias using real-world electronic health records,

Reference 25

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Observation 7a8bebc8-a050-4d18-bf5d-5f19b4bcf731 · outbound

This paper cites A deep learning approach for predicting multiple sclerosis,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification A deep learning approach for predicting multiple sclerosis,

Reference 26

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Observation c17e66bf-3a3d-4181-a93d-e968bc5be0ae · outbound

This paper cites Multimodal deep learning for integrating chest radiographs and clinical parameters: A case for transformers,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Multimodal deep learning for integrating chest radiographs and clinical parameters: A case for transformers,

Reference 27

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Observation cf4e45fb-023a-4df0-b333-3cc0c8c6c137 · outbound

This paper cites Enhancing early parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Enhancing early parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database,

Reference 28

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Observation cf2d4e35-24e7-4401-99cf-03e2b93ad97f · outbound

This paper cites Deep learning integrates histopathology and proteogenomics at a pan-cancer level,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Deep learning integrates histopathology and proteogenomics at a pan-cancer level,

Reference 29

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Observation 50a5a8e0-a97b-4e2c-af88-19c7f2c80bcb · outbound

This paper cites Towards Understanding Mixture of Experts in Deep Learning.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Towards Understanding Mixture of Experts in Deep Learning

Reference 30

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Observation 2453c7fe-990f-4bfd-960c-28cd6caf7c94 · outbound

This paper cites Med-moe: Mixture of domain-specific experts for lightweight medical vision- language models,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Med-moe: Mixture of domain-specific experts for lightweight medical vision- language models,

Reference 31

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Observation d9ef645a-a162-4474-8207-6b40f8315893 · outbound

This paper cites Flex-moe: Modeling arbitrary modality combination via the flexible mixture-of-experts,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Flex-moe: Modeling arbitrary modality combination via the flexible mixture-of-experts,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:13:40.059372Z

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.

source=pdf_text observed=2026-08-07T00:13:38.299227Z digest=sha256:b0324a37527155949262c5f0a9321aca7408a52fb8110b14b29ca90f10e0e949

Observation e5294a77-8887-4b56-9733-a7dbd6498673 · outbound

This paper cites Reduced volume of the putamen in rem sleep behavior disorder patients,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Reduced volume of the putamen in rem sleep behavior disorder patients,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:13:39.882941Z

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.

source=pdf_text observed=2026-08-07T00:13:38.425438Z digest=sha256:938f77e3f1e899047ba1689d3dbdc4a0a16a9c3248d453311b97a7ff3e7868c6

Observation 74348750-455c-403f-a555-c4501b99a461 · outbound

This paper cites Dynamic image for 3d mri image alzheimer’s disease classification,.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification Dynamic image for 3d mri image alzheimer’s disease classification,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:13:39.624420Z

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.

source=pdf_text observed=2026-08-07T00:13:38.614070Z digest=sha256:4c4fca7ffc99c281cfefc4d1e69641c75f87bea01311a25f7f6ba49ec69c0a7f

Observation 71e041dc-0cac-4b11-9cf5-e226a2fb3f6b · outbound

This paper cites A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks.

NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification A Comprehensive Study of Alzheimer's Disease Classification Using Convolutional Neural Networks

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-07T00:13:39.382747Z

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.

source=pdf_text observed=2026-08-07T00:13:38.761261Z digest=sha256:a22dd67e500e2b29fd8d858383e3036df229721e89d543b737bd6e52bb5de7ef

Pith citing papers

Observation ffb9938b-2ae0-4eba-b2cd-1e63a45105bb · inbound

Lightweight Chunk Selection for Mobile Retrieval-Augmented Generation cites this paper.

Lightweight Chunk Selection for Mobile Retrieval-Augmented Generation NeuroMoE: A Transformer-Based Mixture-of-Experts Framework for Multi-Modal Neurological Disorder Classification

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-08-06T00:45:28.111193Z

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.

source=pdf_text observed=2026-08-06T00:45:24.787032Z digest=sha256:992c491454801c24b3c8c3bea073b9369c221db1d60a60394cf377039d6a5317