Paper Citation Record · LEDGER

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis

As of 23 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2507.08050.

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

pith.paper-citation-record.v1
2507.08050 v1

Coverage vector

measured 33 of 33 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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External citation measurements

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Outbound references

Observation f3bf6e9b-295d-4e8e-b597-e0c7cb4f2391 · outbound

This paper cites Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Assessing the value of integrating national longitudinal shopping data into respiratory disease forecasting models

Reference 1

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Observation 0ba71f72-bdfb-4287-a623-35f86dd3e8ea · outbound

This paper cites Global impact of respiratory disease: what can we do, together, to make a difference? Chest 2022;161(5):1153–1154.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Global impact of respiratory disease: what can we do, together, to make a difference? Chest 2022;161(5):1153–1154

Reference 2

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Observation 613552d6-11e2-4519-b14f-65d0aa19db25 · outbound

This paper cites Patient exposure from radiologic and nuclear medicine procedures in the united states: procedure volume 23 and effective dose for the period 2006–2016.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Patient exposure from radiologic and nuclear medicine procedures in the united states: procedure volume 23 and effective dose for the period 2006–2016

Reference 3

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Observation 9c322f9e-8ec4-499a-9012-91721ca084e7 · outbound

This paper cites Machine-learning-based multiple ab- normality prediction with large-scale chest computed tomography volumes.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Machine-learning-based multiple ab- normality prediction with large-scale chest computed tomography volumes

Reference 4

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This paper cites Data science and the role of artificial intelli- gence in achieving the fast diagnosis of COVID-19.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Data science and the role of artificial intelli- gence in achieving the fast diagnosis of COVID-19

Reference 5

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Observation 665e3de7-2017-455e-9a29-d2b96b6c4c64 · outbound

This paper cites Focal liver lesion diagnosis with deep learning and multistage CT imaging.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Focal liver lesion diagnosis with deep learning and multistage CT imaging

Reference 6

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correction dated 2025-06-18. Source: crossref record 10.1038/s41467-025-61097-2->10.1038/s41467-024-51260-6:correction, observed 2026-07-11T03:02:01.968524+00:00. This notice travels one citation hop only.

Observation dc51520d-bdcd-4e9a-8c1a-cf26de6cb37e · outbound

This paper cites Ultrasound-based radiomics technology in fetal lung texture analysis prediction of neonatal respiratory morbidity.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Ultrasound-based radiomics technology in fetal lung texture analysis prediction of neonatal respiratory morbidity

Reference 7

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This paper cites Evolutionary algorithms for automatic lung disease detection.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Evolutionary algorithms for automatic lung disease detection

Reference 8

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Observation a2dc6eda-4562-454f-9172-9aca43153486 · outbound

This paper cites https://synapse.koreamed.org/ pdf/10.4258/hir.2016.22.4.351.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis https://synapse.koreamed.org/ pdf/10.4258/hir.2016.22.4.351

Reference 9

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Observation 92768961-f3af-41a0-bc77-218edf7ef117 · outbound

This paper cites CoroDet: a deep learning based classifica- tion for COVID-19 detection using chest X-ray images.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis CoroDet: a deep learning based classifica- tion for COVID-19 detection using chest X-ray images

Reference 10

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Observation da68945b-8ebf-4fad-843a-3367bafa5526 · outbound

This paper cites An efficient deep neural network framework for COVID-19 lung infection segmentation.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis An efficient deep neural network framework for COVID-19 lung infection segmentation

Reference 11

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Observation c979e29c-4f7b-40ea-8c99-ec4cfb60e34a · outbound

This paper cites Generalizing from a few examples: a survey on few- shot learning.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Generalizing from a few examples: a survey on few- shot learning

Reference 12

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Observation 26468f17-49f1-4c47-9bb4-5e3b2d644809 · outbound

This paper cites A systematic review of few-shot learning in medical imag- ing.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis A systematic review of few-shot learning in medical imag- ing

Reference 13

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Observation 2de8aa35-122a-40fd-b94a-2ba14d27d43c · outbound

This paper cites Few-shot learning for CT scan based COVID-19 diag- nosis.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Few-shot learning for CT scan based COVID-19 diag- nosis

Reference 14

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Observation 134d6e9c-4b6a-4116-b607-9cf36931655c · outbound

This paper cites Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning

Reference 15

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Observation a7b23b51-88cc-4002-9685-7bc33a7bdf9f · outbound

This paper cites Time series modeling and forecasting of epi- demic spreading processes using deep transfer learning.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Time series modeling and forecasting of epi- demic spreading processes using deep transfer learning

Reference 16

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Observation 740fc053-d66e-4a01-b6a6-13fcbb531d96 · outbound

This paper cites MetaCOVID: a siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis MetaCOVID: a siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients

Reference 17

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Observation fa49e60e-e945-4450-a901-55ee79c2c1c6 · outbound

This paper cites Meta-SGD: Learning to Learn Quickly for Few-Shot Learning.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Meta-SGD: Learning to Learn Quickly for Few-Shot Learning

Reference 18

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Observation 7c323676-0299-40b2-b5d5-81124c02d80c · outbound

This paper cites Secure, privacy-preserving and fed- erated machine learning in medical imaging.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Secure, privacy-preserving and fed- erated machine learning in medical imaging

Reference 19

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This paper cites Federated learning for COVID-19 screening from chest X-ray images.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Federated learning for COVID-19 screening from chest X-ray images

Reference 20

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Observation 5f0bffb8-5d03-4460-9425-f14ca9285044 · outbound

This paper cites The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis The Secret Revealer: Generative Model-Inversion Attacks Against Deep Neural Networks

Reference 21

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An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Model inversion attacks that exploit confidence information and basic countermeasures

Reference 22

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This paper cites PPFLHE: a privacy-preserving federated learning scheme with homomorphic encryption for healthcare data.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis PPFLHE: a privacy-preserving federated learning scheme with homomorphic encryption for healthcare data

Reference 23

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Observation bb80f829-2a59-4b93-84f8-c20122d8f6fc · outbound

This paper cites Federated learning-empowered disease diagnosis mech- anism in the internet of medical things: from the privacy-preservation perspec- tive.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Federated learning-empowered disease diagnosis mech- anism in the internet of medical things: from the privacy-preservation perspec- tive

Reference 24

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This paper cites Communication-efficient learning of deep networks from decentralized data.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Communication-efficient learning of deep networks from decentralized data

Reference 25

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Observation e0b1152a-380c-413b-ae48-a217135c1a02 · outbound

This paper cites Our data, ourselves: privacy via dis- tributed noise generation.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Our data, ourselves: privacy via dis- tributed noise generation

Reference 26

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Observation a440e313-4c00-4d86-ae14-34849aaac4d2 · outbound

This paper cites Differential privacy for statistics: what we know and what we want to learn.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Differential privacy for statistics: what we know and what we want to learn

Reference 27

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An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Deep learning with differential privacy

Reference 28

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This paper cites Can ai help in screening viral and COVID-19 pneumonia? IEEE Access 2020;8:132665–132676.https://doi.org/10.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Can ai help in screening viral and COVID-19 pneumonia? IEEE Access 2020;8:132665–132676.https://doi.org/10

Reference 29

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This paper cites Exploring the effect of image enhance- ment techniques on COVID-19 detection using chest X-ray images.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Exploring the effect of image enhance- ment techniques on COVID-19 detection using chest X-ray images

Reference 30

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An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Deep learning for reliable classifica- tion of COVID-19, MERS, and SARS from chest X-ray images

Reference 31

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This paper cites COVID-CT-Dataset: A CT Scan Dataset about COVID-19.

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis COVID-CT-Dataset: A CT Scan Dataset about COVID-19

Reference 32

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An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis Model-agnostic meta-learning for fast adaptation of deep networks

Reference 33

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Pith citing papers

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