scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis | Paper Citation Record

Observation 8468be0a-830f-46a0-8f20-1b1dc20fb6b0 · outbound

This paper cites Genetic sequencing provides detailed information about an individual's genome at a microscopic level, including specific genetic variations and genetic risk -related data [2, 3].

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Genetic sequencing provides detailed information about an individual's genome at a microscopic level, including specific genetic variations and genetic risk -related data [2, 3]

Reference 1

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Observation a90ac7df-ae2f-4e12-bab5-fe6431dcb654 · outbound

This paper cites Recent research in AD prediction using neuroimaging data incorporates advanced methodologies that include network techniques and machine learning algorithms.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Recent research in AD prediction using neuroimaging data incorporates advanced methodologies that include network techniques and machine learning algorithms

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.839813Z

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Observation dec9873f-57cb-416c-940f-799ffeed788d · outbound

This paper cites 1" to males and.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis 1" to males and

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.828695Z

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Observation 2488ab24-1c81-4be0-a6a7-8e9271b79787 · outbound

This paper cites In our study, we utilized multiple datasets to provide a comprehensive analysis of AD.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis In our study, we utilized multiple datasets to provide a comprehensive analysis of AD

Reference 4

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Observation 84d13728-19c4-476c-8218-b1047bc6f51a · outbound

This paper cites Comprehensive review on Alzheimer’s disease: causes and treatment,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Comprehensive review on Alzheimer’s disease: causes and treatment,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.804929Z

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Observation 3e39c4ce-ee35-4e3e-a850-6885feaf5eae · outbound

This paper cites Genetic differences in the immediate transcriptome response to stress predict risk -related brain function and psychiatric disorders,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Genetic differences in the immediate transcriptome response to stress predict risk -related brain function and psychiatric disorders,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.733980Z

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Observation cdc034d2-b219-4e79-ad77-e299fa0f7fb8 · outbound

This paper cites MCAN: multimodal causal adversarial networks for dynamic effective connectivity learning from fMRI and EEG data,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis MCAN: multimodal causal adversarial networks for dynamic effective connectivity learning from fMRI and EEG data,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.668640Z

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Observation e069853a-974d-4d70-ab45-ac3dd80b17d8 · outbound

This paper cites Joint sparse representation of brain activity patterns in multi-task fMRI data,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Joint sparse representation of brain activity patterns in multi-task fMRI data,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.592533Z

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Observation 379d511a-fdf0-4cf6-a19a-ea5fd942e447 · outbound

This paper cites Interpretable cognitive ability prediction: A comprehensive gated graph transformer framework for analyzing functional brain networks,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Interpretable cognitive ability prediction: A comprehensive gated graph transformer framework for analyzing functional brain networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.528974Z

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Observation 4121e86d-124c-4a22-a4e2-f07b3294ef39 · outbound

This paper cites Identifying autism spectrum disorder from resting-state fMRI using deep belief network,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Identifying autism spectrum disorder from resting-state fMRI using deep belief network,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.517953Z

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Observation 6b209070-a227-4de5-9ded-832f167f7368 · outbound

This paper cites GATE: Graph CCA for temporal self -supervised learning for label -efficient fMRI analysis,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis GATE: Graph CCA for temporal self -supervised learning for label -efficient fMRI analysis,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.506794Z

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Observation 7e6dbdc5-cea2-4208-8c8a-dc2bb6323afb · outbound

This paper cites Modeling task fMRI data via deep convolutional autoencoder,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Modeling task fMRI data via deep convolutional autoencoder,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.495261Z

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Observation f8e8f855-c830-49cf-bae9-9dad92402b82 · outbound

This paper cites Federated multi-task learning for joint diagnosis of multiple mental disorders on MRI scans,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Federated multi-task learning for joint diagnosis of multiple mental disorders on MRI scans,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.483068Z

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Observation 34f94de9-0d84-40fd-a851-4550d7f22089 · outbound

This paper cites Multi -hypergraph learning -based brain functional connectivity analysis in fMRI data,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Multi -hypergraph learning -based brain functional connectivity analysis in fMRI data,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.471135Z

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Observation 352e6d42-bd4d-4a45-9002-9210cbcde1ac · outbound

This paper cites Estimating effective connectivity by recurrent generative adversarial networks,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Estimating effective connectivity by recurrent generative adversarial networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.458866Z

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Observation 10b870e6-5e99-47b6-8a39-7d1f0efecc9b · outbound

This paper cites Multitask Learning for Joint Diagnosis of Multiple Mental Disorders in Resting-State fMRI,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Multitask Learning for Joint Diagnosis of Multiple Mental Disorders in Resting-State fMRI,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.445313Z

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Observation 233bd122-573d-4a72-95a7-1d6670190fed · outbound

This paper cites Attention -like multimodality fusion with data augmentation for diagnosis of mental disorders using MRI,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Attention -like multimodality fusion with data augmentation for diagnosis of mental disorders using MRI,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.432323Z

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Observation abe129c0-e4c7-4ee9-bd1e-98f8898f8546 · outbound

This paper cites Toward best practices for imaging transcriptomics of the human brain,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Toward best practices for imaging transcriptomics of the human brain,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.420202Z

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Observation 0b0d1499-d58d-4398-88b3-356c81594127 · outbound

This paper cites Spatial–temporal co-attention learning for diagnosis of mental disorders from resting -state fMRI data,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Spatial–temporal co-attention learning for diagnosis of mental disorders from resting -state fMRI data,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.408238Z

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Observation d4318920-7e94-4b92-955e-3def3538d953 · outbound

This paper cites Source free semi-supervised transfer learning for diagnosis of mental disorders on fmri scans,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Source free semi-supervised transfer learning for diagnosis of mental disorders on fmri scans,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.376942Z

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Observation ed9e7805-2880-4c04-99cc-1ff5258bfce3 · outbound

This paper cites A critical appraisal of imaging transcriptomics,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis A critical appraisal of imaging transcriptomics,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.312453Z

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Observation 559a4d7f-5c5b-441e-ab1b-7a3e650414dd · outbound

This paper cites The Allen Human Brain Atlas: comprehensive gene expression mapping of the human brain,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis The Allen Human Brain Atlas: comprehensive gene expression mapping of the human brain,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.221647Z

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Observation 5aa49571-a186-4048-8ea0-5c47771304d7 · outbound

This paper cites Single-cell transcriptomic analysis of Alzheimer’s disease,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Single-cell transcriptomic analysis of Alzheimer’s disease,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.158491Z

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Observation 1eac7ef1-3ed1-42ed-8e14-7965a172f870 · outbound

This paper cites A study of feature extraction for Alzheimer's disease based on resting-state fMRI.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis A study of feature extraction for Alzheimer's disease based on resting-state fMRI

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.146687Z

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Observation 668dc3b6-536b-4116-a48f-c0ed984b1cc5 · outbound

This paper cites A supervised method to assist the diagnosis and monitor progression of Alzheimer's disease using data from an fMRI experiment,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis A supervised method to assist the diagnosis and monitor progression of Alzheimer's disease using data from an fMRI experiment,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.134366Z

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Observation 729585b2-c9ab-4749-9b4f-737116a7018e · outbound

This paper cites Identification of the early stage of Alzheimer's disease using structural MRI and resting -state fMRI,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Identification of the early stage of Alzheimer's disease using structural MRI and resting -state fMRI,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.123268Z

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Observation 5331d406-b9d4-4874-88ac-abf325be49c2 · outbound

This paper cites Multi-scale time-series kernel-based learning method for brain disease diagnosis,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Multi-scale time-series kernel-based learning method for brain disease diagnosis,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.112354Z

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Observation 3f2aff5f-7f54-43b4-990c-8eb68c5c585c · outbound

This paper cites Analysis of Alzheimer’s disease based on the random neural network cluster in fMRI,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Analysis of Alzheimer’s disease based on the random neural network cluster in fMRI,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.100891Z

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Observation 8faea9ab-97ee-42a8-bbef-58f6ce0c698e · outbound

This paper cites Improved brain age estimation with slice - based set networks.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Improved brain age estimation with slice - based set networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.089272Z

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Observation 44a3ac02-5eb9-4a41-bef6-340da012e83d · outbound

This paper cites Analysis of features of Alzheimer’s disease: Detection of early stage from functional brain changes in magnetic resonance images using a finetuned ResNet18 network,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Analysis of features of Alzheimer’s disease: Detection of early stage from functional brain changes in magnetic resonance images using a finetuned ResNet18 network,

Reference 30

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Observation b6ba0f80-4919-4458-9815-e9df21fc222f · outbound

This paper cites Multimodal data fusion of deep learning and dynamic functional connectivity features to predict Alzheimer’s disease progression.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Multimodal data fusion of deep learning and dynamic functional connectivity features to predict Alzheimer’s disease progression

Reference 31

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Observation 2acbd7cc-bda0-4ef1-b31b-77701eacbedc · outbound

This paper cites Classification of Alzheimer’s Disease and Mild - Cognitive Impairment Base on High -Order Dynamic Functional Connectivity at Different Frequency Band,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Classification of Alzheimer’s Disease and Mild - Cognitive Impairment Base on High -Order Dynamic Functional Connectivity at Different Frequency Band,

Reference 32

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Observation f4ef56bf-c8d9-45d6-bc38-d74a1407268c · outbound

This paper cites Mixture -of-experts with expert choice routing,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Mixture -of-experts with expert choice routing,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:41.026146Z

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Observation fc7f3d13-453a-4c4a-a5fe-3c6a01d499e3 · outbound

This paper cites Protgnn: Towards self -explaining graph neural networks.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Protgnn: Towards self -explaining graph neural networks

Reference 34

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Observation 6d1af536-f823-414b-a20f-3a975ae44618 · outbound

This paper cites A survey of monte carlo tree search methods,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis A survey of monte carlo tree search methods,

Reference 35

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Observation b366dc33-a7db-4f4d-b4d3-15ace79c55ba · outbound

This paper cites PLINK: a tool set for whole -genome association and population-based linkage analyses,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis PLINK: a tool set for whole -genome association and population-based linkage analyses,

Reference 36

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Observation 4633a6f0-132b-4ec2-a6ad-2cf23d48e978 · outbound

This paper cites SCENIC: single -cell regulatory network inference and clustering,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis SCENIC: single -cell regulatory network inference and clustering,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.818875Z

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Observation 2a32cb8d-21e4-4bb0-bb48-666124bdc280 · outbound

This paper cites Integrated multimodal cell atlas of Alzheimer’s disease,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Integrated multimodal cell atlas of Alzheimer’s disease,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.808332Z

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Observation 23105580-a2bc-4f31-9cd0-077e9a306d58 · outbound

This paper cites The Alzheimer’s disease neuroimaging initiative,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis The Alzheimer’s disease neuroimaging initiative,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.797633Z

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Observation 3d9d86f2-baf3-432d-9e90-90fe6b91d847 · outbound

This paper cites The Alzheimer's disease neuroimaging initiative: progress report and future plans,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis The Alzheimer's disease neuroimaging initiative: progress report and future plans,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.785878Z

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Observation 464a99d4-88f1-43eb-bae8-4e9afffdeb66 · outbound

This paper cites an unresolved cited work.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Unresolved cited work

Reference 41

Resolution: unresolved; raw_fallback, observed 2026-08-09T11:48:40.774280Z

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Observation 99fc0299-ffa6-44e6-92fb-cc8a91d38aa3 · outbound

This paper cites Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Comparison of the diagnostic accuracy of resting-state fMRI driven machine learning algorithms in the detection of mild cognitive impairment,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.762778Z

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Observation ed6d96ef-3232-45f8-9af3-0cfd3831c506 · outbound

This paper cites The identification of Alzheimer’s disease using functional connectivity between activity voxels in resting -state fMRI data,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis The identification of Alzheimer’s disease using functional connectivity between activity voxels in resting -state fMRI data,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.751182Z

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

Observation 5d705f25-57a4-4956-b2cf-c620a3722f5c · outbound

This paper cites Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Gaussian process classification of Alzheimer's disease and mild cognitive impairment from resting-state fMRI,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.738194Z

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Observation 2b1bc8fd-1d84-49f9-9231-d055d9e73917 · outbound

This paper cites Classification of Alzheimer’s disease based on core -large scale brain network using multilayer extreme learning machine,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Classification of Alzheimer’s disease based on core -large scale brain network using multilayer extreme learning machine,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.726243Z

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Observation b871c37b-e51c-4346-a1ac-6cbc3c83ca7d · outbound

This paper cites an unresolved cited work.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Unresolved cited work

Reference 46

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Observation 6fda909d-5675-4656-8b25-b9fdc0945270 · outbound

This paper cites Classification of brain disorders in rs -fMRI via local-to-global graph neural networks,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Classification of brain disorders in rs -fMRI via local-to-global graph neural networks,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.701812Z

Source-reported events for the cited work

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Observation 0b2223ad-62df-47ec-8591-a1495442256b · outbound

This paper cites Remote sensing image classification based on a cross -attention mechanism and graph convolution,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Remote sensing image classification based on a cross -attention mechanism and graph convolution,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.482065Z

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This paper cites Grad-CAM: Why did you say that?.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Grad-CAM: Why did you say that?

Reference 49

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This paper cites Integration of multimodal data for deciphering brain disorders,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Integration of multimodal data for deciphering brain disorders,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T11:48:40.314928Z

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This paper cites Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Quantitative systems pharmacology in neuroscience: Novel methodologies and technologies,

Reference 51

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This paper cites Current status of tissue clearing and the path forward in neuroscience,.

scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Current status of tissue clearing and the path forward in neuroscience,

Reference 52

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scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis Cross-modal contrastive learning for text-to- image generation

Reference 53

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scBIT: Integrating Single-cell Transcriptomic Data into fMRI-based Prediction for Alzheimer's Disease Diagnosis UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning

Reference 54

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