Paper Citation Record · LEDGER

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning

As of 13 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.10567.

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

pith.paper-citation-record.v1
2412.10567 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:53:14.403066Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

31 of 31 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 751f3abd-730a-4001-b62b-9ab2a49713e2 · outbound

This paper cites Ai-driven stylization of 3d environments, 2024.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Ai-driven stylization of 3d environments, 2024

Reference 1

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Source-reported events for the cited work

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Observation ccd4d7a3-be7b-4fed-b737-536bb4ba1008 · outbound

This paper cites Graphical structural learning of rs-fmri data in heavy smokers.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Graphical structural learning of rs-fmri data in heavy smokers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.629029Z

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Observation 3c5687b1-0042-4ce5-94df-28e57f8f941d · outbound

This paper cites Pcm microcapsules applicable foam to improve the properties of thermal insulation and energy storage for cement-based material.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Pcm microcapsules applicable foam to improve the properties of thermal insulation and energy storage for cement-based material

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.622386Z

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Observation 5a03fb10-9d05-42f0-b72a-eec76d19c162 · outbound

This paper cites Green building material with superior thermal insulation and energy storage properties fabricated by paraffin and foam cement composite.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Green building material with superior thermal insulation and energy storage properties fabricated by paraffin and foam cement composite

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.615624Z

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Observation 7a7b8515-16e8-44c8-9591-d663c2bfb5ce · outbound

This paper cites Artificial intelligence aspect of transportation analysis using large scale systems.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Artificial intelligence aspect of transportation analysis using large scale systems

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.608608Z

Source-reported events for the cited work

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Observation 0b5e6a45-5215-45a2-b03c-8d69e065561e · outbound

This paper cites AR Overlay: Training Image Pose Estimation on Curved Surface in a Synthetic Way.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning AR Overlay: Training Image Pose Estimation on Curved Surface in a Synthetic Way

Reference 6

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Source-reported events for the cited work

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Observation 21a60191-3c0b-40dd-9690-f26a94008657 · outbound

This paper cites Learning from teaching regularization: Generalizable correlations should be easy to imitate.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Learning from teaching regularization: Generalizable correlations should be easy to imitate

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.601936Z

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Observation 57b50227-f0f4-4065-b014-9f6803db5de8 · outbound

This paper cites Tie memories to e- souvenirs: Personalized souvenirs with augmented reality for interactive learning in the museum.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Tie memories to e- souvenirs: Personalized souvenirs with augmented reality for interactive learning in the museum

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.594987Z

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Observation 007aca79-e674-400b-b93c-731695845a9d · outbound

This paper cites 6: Simultaneous tracking, tagging and mapping for augmented reality.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning 6: Simultaneous tracking, tagging and mapping for augmented reality

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.587972Z

Source-reported events for the cited work

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Observation c7a69c33-8094-407f-93b6-ab9f0c524885 · outbound

This paper cites Tie memories to e-souvenirs: Hybrid tangible ar souvenirs in the museum.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Tie memories to e-souvenirs: Hybrid tangible ar souvenirs in the museum

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.581135Z

Source-reported events for the cited work

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

Observation 810cadd6-f8d6-42df-9ce5-b6ebe1d4f0dd · outbound

This paper cites Predicting 30-day hospital readmission in medicare patients: Insights from an lstm deep learning model.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Predicting 30-day hospital readmission in medicare patients: Insights from an lstm deep learning model

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.574088Z

Source-reported events for the cited work

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

Observation 033f6fb7-0253-42b3-ba89-53458f5dcf1f · outbound

This paper cites A comparative study of machine learning approaches for diabetes risk prediction: Insights from shap and feature importance.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning A comparative study of machine learning approaches for diabetes risk prediction: Insights from shap and feature importance

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.567240Z

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Observation e4b34f42-c050-49e4-a3bc-c3574fae4a0b · outbound

This paper cites Lingcn: Structural linearized graph convolutional network for homomorphically encrypted inference.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Lingcn: Structural linearized graph convolutional network for homomorphically encrypted inference

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.560342Z

Source-reported events for the cited work

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Observation d7a5a2c5-3680-41af-b2b5-0c345c88f48b · outbound

This paper cites Maxk-gnn: Extremely fast gpu kernel design for accelerating graph neural networks training.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Maxk-gnn: Extremely fast gpu kernel design for accelerating graph neural networks training

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.553420Z

Source-reported events for the cited work

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Observation caaa6883-5c87-4a12-9478-b5c165fae7a5 · outbound

This paper cites A systematic review of publications assessing reliability and validity of the behavioral risk factor surveillance system (brfss), 2004–2011.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning A systematic review of publications assessing reliability and validity of the behavioral risk factor surveillance system (brfss), 2004–2011

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.546713Z

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Observation 35134c71-6fcd-4a46-b1cf-cc9ecabe6594 · outbound

This paper cites Harnessing XGBoost for robust biomarker selection of obsessive-compulsive disor- der (OCD) from adolescent brain cognitive development (ABCD) data.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Harnessing XGBoost for robust biomarker selection of obsessive-compulsive disor- der (OCD) from adolescent brain cognitive development (ABCD) data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.539931Z

Source-reported events for the cited work

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

Observation f08c95ca-d322-4fd9-86cb-3c4d5f4d8ffc · outbound

This paper cites A mixed- heuristic quantum-inspired simplified swarm optimization algorithm for scheduling of real-time tasks in the multiprocessor system.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning A mixed- heuristic quantum-inspired simplified swarm optimization algorithm for scheduling of real-time tasks in the multiprocessor system

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.533053Z

Source-reported events for the cited work

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

Observation 4ba4863b-acca-4ca1-ae6d-a890f1f874c3 · outbound

This paper cites Research on prediction recommendation system based on improved markov model.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Research on prediction recommendation system based on improved markov model

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.526045Z

Source-reported events for the cited work

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Observation 16fde95d-9ed6-4834-ae25-f80b0746b080 · outbound

This paper cites Accel- gcn: High-performance gpu accelerator design for graph convolution networks.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Accel- gcn: High-performance gpu accelerator design for graph convolution networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.519256Z

Source-reported events for the cited work

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

Observation 8ec1046f-e7ee-4d90-aac4-f54b3d878aa0 · outbound

This paper cites Influencing factors of housing price in new york-analysis: Based on excel multi-regression model.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Influencing factors of housing price in new york-analysis: Based on excel multi-regression model

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.512601Z

Source-reported events for the cited work

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

Observation 0e3f501f-ddcd-49f9-970e-f164889cf815 · outbound

This paper cites Analysis of financial risk behavior prediction using deep learning and big data algorithms, 2024.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Analysis of financial risk behavior prediction using deep learning and big data algorithms, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.505564Z

Source-reported events for the cited work

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

Observation d008ada4-d995-4c76-b8d7-d5f12a949beb · outbound

This paper cites Long-term trends in the distribution of ocean chlorophyll.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Long-term trends in the distribution of ocean chlorophyll

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.498534Z

Source-reported events for the cited work

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

Observation 80f27cae-4800-4a82-b33d-c43bfbf7638c · outbound

This paper cites Comparative analysis of bayesian networks for breast cancer classifica- tion: Naive bayes vs.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Comparative analysis of bayesian networks for breast cancer classifica- tion: Naive bayes vs

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.491706Z

Source-reported events for the cited work

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Observation a15c2c31-3a40-420b-8179-b36e886dbdaf · outbound

This paper cites CU-Net: A U- Net Architecture for Efficient Brain-Tumor Segmentation on BraTS 2019 Dataset.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning CU-Net: A U- Net Architecture for Efficient Brain-Tumor Segmentation on BraTS 2019 Dataset

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.484618Z

Source-reported events for the cited work

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

Observation 04b635e0-20c6-44fd-bc7d-ac5ce83c7d58 · outbound

This paper cites Optimization and application of cloud-based deep learning architecture for multi-source data prediction, 2024.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Optimization and application of cloud-based deep learning architecture for multi-source data prediction, 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.477371Z

Source-reported events for the cited work

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Observation 52350448-f754-43e4-861d-90d5d72e0d2c · outbound

This paper cites Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-11T15:53:14.426685Z

Source-reported events for the cited work

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Observation 1da8a023-5ff6-4db2-bb76-6d0d461a40ca · outbound

This paper cites Deep learning solutions for pneumonia detection: Per- formance comparison of custom and transfer learning models.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Deep learning solutions for pneumonia detection: Per- formance comparison of custom and transfer learning models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.469646Z

Source-reported events for the cited work

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Observation 1a656f43-76c5-42c8-a709-725ef859f86f · outbound

This paper cites Adapi: Facilitating dnn model adaptivity for efficient private inference in edge computing.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Adapi: Facilitating dnn model adaptivity for efficient private inference in edge computing

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.462410Z

Source-reported events for the cited work

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

Observation 2e675009-2620-44d1-92c7-dea8c77aceb8 · outbound

This paper cites Optimizing distributed networking with big data scheduling and cloud computing.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Optimizing distributed networking with big data scheduling and cloud computing

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.455226Z

Source-reported events for the cited work

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

Observation b0db7e79-3758-47d6-a288-cb01e1673988 · outbound

This paper cites Twitter sentiment analysis of covid vaccines.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Twitter sentiment analysis of covid vaccines

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.448119Z

Source-reported events for the cited work

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

Observation 648167c1-b94d-4b80-b47c-e183a30d9581 · outbound

This paper cites Demonstration of chromocloth: Re-programmable multi-color textures through flexible and portable light source.

Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning Demonstration of chromocloth: Re-programmable multi-color textures through flexible and portable light source

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T15:53:14.440607Z

Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.