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Paper Citation Record · LEDGER

ROOFS: RObust biOmarker Feature Selection

As of 20 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 2 inbound Pith citation observations for arXiv:2601.05151.

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

pith.paper-citation-record.v1
2601.05151 v3

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:50:20.103359Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:18:34.306896Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T00:04:06.980292Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact16
  • verified fuzzy0
  • unresolved40
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 34b75565-b2dc-48b7-af7c-7434cc55fd31 · outbound

This paper cites An introduction to variable and feature selection.Journal of Machine Learning Research, 3(Mar):1157–1182, 2003.

ROOFS: RObust biOmarker Feature Selection An introduction to variable and feature selection.Journal of Machine Learning Research, 3(Mar):1157–1182, 2003

Reference 1

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Observation 4f538734-1d65-44da-a3ae-f1921c47cac4 · outbound

This paper cites Trevino, Jiliang Tang, and Huan Liu.

ROOFS: RObust biOmarker Feature Selection Trevino, Jiliang Tang, and Huan Liu

Reference 2

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Observation 8522ff85-de53-4de2-ac1f-cc65e0f75d77 · outbound

This paper cites Stability of feature selection algorithms.

ROOFS: RObust biOmarker Feature Selection Stability of feature selection algorithms

Reference 3

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Observation 2f3c3223-3a40-4b0d-9fda-5d5b718793d7 · outbound

This paper cites The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures.PLOS ONE, 6(12):e28210, 2011.

ROOFS: RObust biOmarker Feature Selection The influence of feature selection methods on accuracy, stability and interpretability of molecular signatures.PLOS ONE, 6(12):e28210, 2011

Reference 4

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Observation c6d14b9e-ee96-4095-bb75-ef7cd806d39b · outbound

This paper cites Variable selection – a review and recommendations for the practicing statistician.Biometrical Journal, 60(3):431–449, 2018.

ROOFS: RObust biOmarker Feature Selection Variable selection – a review and recommendations for the practicing statistician.Biometrical Journal, 60(3):431–449, 2018

Reference 5

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Observation 53c3e933-f50e-4f87-bc7d-51f2357748ce · outbound

This paper cites Benchmark for filter methods for feature selection in high-dimensional classification data.Computational Statistics & Data Analysis, 143:106839, 2020.

ROOFS: RObust biOmarker Feature Selection Benchmark for filter methods for feature selection in high-dimensional classification data.Computational Statistics & Data Analysis, 143:106839, 2020

Reference 6

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Observation 89ed7d42-6ebd-4811-bf0f-4d514e400833 · outbound

This paper cites Benchmarking feature projection methods in radiomics.Scientific Reports, 15(1):32368, sept.

ROOFS: RObust biOmarker Feature Selection Benchmarking feature projection methods in radiomics.Scientific Reports, 15(1):32368, sept

Reference 7

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Observation a2c9b27d-5b58-4d4c-8d24-ffc2d353911d · outbound

This paper cites Effect of subset size on the stability of feature selection for gene expression data.

ROOFS: RObust biOmarker Feature Selection Effect of subset size on the stability of feature selection for gene expression data

Reference 8

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Observation 65f3328e-5e5e-4617-bc24-efd87e1b7ea3 · outbound

This paper cites Evaluation of clinical prediction models (part 1): from development to external validation.BMJ, 384, 2024.

ROOFS: RObust biOmarker Feature Selection Evaluation of clinical prediction models (part 1): from development to external validation.BMJ, 384, 2024

Reference 9

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Observation c99cb188-8a21-49bb-8318-a0a71ff48c76 · outbound

This paper cites Filter Methods for Feature Selection in Supervised Machine Learning Applications -- Review and Benchmark.

ROOFS: RObust biOmarker Feature Selection Filter Methods for Feature Selection in Supervised Machine Learning Applications -- Review and Benchmark

Reference 10

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Observation 4b113157-3191-4bd6-a14a-e080bfba053c · outbound

This paper cites Rintala, and Vittorio Fortino.

ROOFS: RObust biOmarker Feature Selection Rintala, and Vittorio Fortino

Reference 11

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Observation 2a1b0209-fedb-451b-b68f-21c4321dd895 · outbound

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ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 12

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Observation 5bced565-52f8-4b17-b5ef-c40c91058d07 · outbound

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ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 13

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ac5f7031-a9df-440f-882e-1f6b94807b2e · outbound

This paper cites Benchmark study of feature selection strategies for multi-omics data.BMC Bioinformatics, 23(1):412, October 2022.

ROOFS: RObust biOmarker Feature Selection Benchmark study of feature selection strategies for multi-omics data.BMC Bioinformatics, 23(1):412, October 2022

Reference 14

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Observation 4ce0769f-78f5-4ef3-85e6-a4acc8c53870 · outbound

This paper cites Benchmark of filter methods for feature selection in high-dimensional gene expression survival data.Briefings in Bioinformatics, 23(1):bbab354, January 2022.

ROOFS: RObust biOmarker Feature Selection Benchmark of filter methods for feature selection in high-dimensional gene expression survival data.Briefings in Bioinformatics, 23(1):bbab354, January 2022

Reference 15

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Observation 0dd0759d-06c2-47dc-9140-5906629edf20 · outbound

This paper cites Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer.BMC Bioinformatics, 23 (3):153, April 2022.

ROOFS: RObust biOmarker Feature Selection Comparison of five supervised feature selection algorithms leading to top features and gene signatures from multi-omics data in cancer.BMC Bioinformatics, 23 (3):153, April 2022

Reference 16

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Observation 06700905-55a2-4b03-8c28-802f623bb6a9 · outbound

This paper cites Ensemble feature selection in medical datasets: Combining filter, wrapper, and embedded feature selection results.Expert Systems, 37(5):e12553, October 2020.

ROOFS: RObust biOmarker Feature Selection Ensemble feature selection in medical datasets: Combining filter, wrapper, and embedded feature selection results.Expert Systems, 37(5):e12553, October 2020

Reference 17

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Observation 48e426e4-f734-48f6-9bd6-96ed5a81a385 · outbound

This paper cites An integrative multimodal machine learning signature of primary resistance to immunotherapy in advanced non-small cell lung cancer: biomarker analysis from the pioneer study.

ROOFS: RObust biOmarker Feature Selection An integrative multimodal machine learning signature of primary resistance to immunotherapy in advanced non-small cell lung cancer: biomarker analysis from the pioneer study

Reference 18

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Observation 4bcf9173-246f-4d79-b092-79fff8bf5a6c · outbound

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ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 19

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Observation aa312658-dd7a-45d4-a63d-979312216c83 · outbound

This paper cites Springer Publishing Company, Incorporated, 2017.

ROOFS: RObust biOmarker Feature Selection Springer Publishing Company, Incorporated, 2017

Reference 20

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Observation 0388a435-3bbf-4fc3-803c-666112c3ae44 · outbound

This paper cites Pedregosa, G.

ROOFS: RObust biOmarker Feature Selection Pedregosa, G

Reference 21

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Observation b207a11e-154f-42df-a79e-8fa726267d2c · outbound

This paper cites Gaudillière, Francois-Xavier Ladant, Franck Verdonk, Ina A.

ROOFS: RObust biOmarker Feature Selection Gaudillière, Francois-Xavier Ladant, Franck Verdonk, Ina A

Reference 22

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Observation 11902670-78e3-403f-a48b-a46eda8b40cb · outbound

This paper cites Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society.

ROOFS: RObust biOmarker Feature Selection Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society

Reference 23

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Observation 563a90c2-67bd-43e5-ab5a-a1cdd71192d1 · outbound

This paper cites The adaptive lasso and its oracle properties.Journal of the American Statistical Association, 101(476): 1418–1429, December 2006.

ROOFS: RObust biOmarker Feature Selection The adaptive lasso and its oracle properties.Journal of the American Statistical Association, 101(476): 1418–1429, December 2006

Reference 24

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Observation ad6b7c8c-9cd6-4cf2-a4e8-f1883e564508 · outbound

This paper cites Exclusive lasso for multi-task feature selection.

ROOFS: RObust biOmarker Feature Selection Exclusive lasso for multi-task feature selection

Reference 25

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Observation 1546108c-7f4b-42a0-a184-93822dd52aea · outbound

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ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 26

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This paper cites Stability selection.Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72(4):417–473, 2010.

ROOFS: RObust biOmarker Feature Selection Stability selection.Journal of the Royal Statistical Society: Series B (Statistical Methodology), 72(4):417–473, 2010

Reference 27

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Observation 03e48076-143a-4f8c-b1c6-d74e0ecf38b3 · outbound

This paper cites Rent—repeated elastic net technique for feature selection.IEEE Access, 9:152333–152346, 2021.

ROOFS: RObust biOmarker Feature Selection Rent—repeated elastic net technique for feature selection.IEEE Access, 9:152333–152346, 2021

Reference 28

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Observation eb5509bc-e327-49f5-98e0-ac2a287cd3d2 · outbound

This paper cites Ultra high-dimensional nonlinear feature selection for big biological data.IEEE Transactions on Knowledge and Data Engineering, 30(7):1352–1365, July 2018.

ROOFS: RObust biOmarker Feature Selection Ultra high-dimensional nonlinear feature selection for big biological data.IEEE Transactions on Knowledge and Data Engineering, 30(7):1352–1365, July 2018

Reference 29

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Observation 88fe62fb-22d1-4beb-b64a-37a387e6c97c · outbound

This paper cites Conditional infomax learning: An integrated framework for feature extraction and fusion.

ROOFS: RObust biOmarker Feature Selection Conditional infomax learning: An integrated framework for feature extraction and fusion

Reference 30

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Observation 06df500f-f349-40d6-a831-d57298932971 · outbound

This paper cites Fast binary feature selection with conditional mutual information.J.

ROOFS: RObust biOmarker Feature Selection Fast binary feature selection with conditional mutual information.J

Reference 31

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ROOFS: RObust biOmarker Feature Selection Meyer and Gianluca Bontempi

Reference 32

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Observation 408993eb-13f1-4ace-b977-dcc2ed12203f · outbound

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ROOFS: RObust biOmarker Feature Selection Data visualization and feature selection: New algorithms for nongaussian data

Reference 33

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Observation a7342b10-b903-47e2-b130-b6b0b21eac55 · outbound

This paper cites Theoretical and empirical analysis of relieff and rrelieff.Machine Learning, 53(1):23–69, October 2003.

ROOFS: RObust biOmarker Feature Selection Theoretical and empirical analysis of relieff and rrelieff.Machine Learning, 53(1):23–69, October 2003

Reference 34

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Observation e3e14f37-2298-4992-8ef8-68e1a3761c71 · outbound

This paper cites Controlling the false discovery rate: A practical and powerful approach to multiple testing.Journal of the Royal Statistical Society.

ROOFS: RObust biOmarker Feature Selection Controlling the false discovery rate: A practical and powerful approach to multiple testing.Journal of the Royal Statistical Society

Reference 35

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Observation 88096446-5ac7-47bb-95da-2b5681c4cc51 · outbound

This paper cites Shapicant: feature selection package based on shap and target permutation.

ROOFS: RObust biOmarker Feature Selection Shapicant: feature selection package based on shap and target permutation

Reference 36

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Observation 74f88985-920e-402d-905a-e8757ff3907c · outbound

This paper cites an unresolved cited work.

ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 37

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Observation b1b965e0-30ab-47c9-86b5-0204613004b1 · outbound

This paper cites Estimating the error rate of a prediction rule: Improvement on cross-validation.Journal of the American Statistical Association, 78(382):316–331, 1983.

ROOFS: RObust biOmarker Feature Selection Estimating the error rate of a prediction rule: Improvement on cross-validation.Journal of the American Statistical Association, 78(382):316–331, 1983

Reference 38

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Observation ba847ab1-140b-4142-8239-88c432e6ae7d · outbound

This paper cites Improvements on cross-validation: The .632+ bootstrap method.Journal of the American Statistical Association, 92(438):548–560, 1997.

ROOFS: RObust biOmarker Feature Selection Improvements on cross-validation: The .632+ bootstrap method.Journal of the American Statistical Association, 92(438):548–560, 1997

Reference 39

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Observation d77e982c-b25b-49e5-a2e1-42e5e82ae409 · outbound

This paper cites Chernick and Robert A.

ROOFS: RObust biOmarker Feature Selection Chernick and Robert A

Reference 40

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Observation 7d147bad-34a2-41d2-afaf-7d02e8acccf9 · outbound

This paper cites an unresolved cited work.

ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 41

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Observation 1ef63d6b-9326-4cb3-8a65-4561ef9c71ba · outbound

This paper cites On the stability of feature selection algorithms.Journal of Machine Learning Research, 18(174):1–54, 2018.

ROOFS: RObust biOmarker Feature Selection On the stability of feature selection algorithms.Journal of Machine Learning Research, 18(174):1–54, 2018

Reference 42

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Observation f7e90dc2-1251-4102-b95f-88d413f9c722 · outbound

This paper cites On model selection consistency of lasso.Journal of Machine Learning Research, 7(90): 2541–2563, 2006.

ROOFS: RObust biOmarker Feature Selection On model selection consistency of lasso.Journal of Machine Learning Research, 7(90): 2541–2563, 2006

Reference 43

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Observation 896bf263-98f7-4eeb-bf1a-f7ddf3c1caf1 · outbound

This paper cites Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations.Genome Biology, 26(1):249, August 2025.

ROOFS: RObust biOmarker Feature Selection Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations.Genome Biology, 26(1):249, August 2025

Reference 44

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Observation 0de2ac7f-2888-4710-8c02-f3c3af8493cb · outbound

This paper cites Riley and Gary S.

ROOFS: RObust biOmarker Feature Selection Riley and Gary S

Reference 45

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Observation bab13529-df15-4e56-bfa8-cfc10052c2e6 · outbound

This paper cites IntechOpen, February 2010.

ROOFS: RObust biOmarker Feature Selection IntechOpen, February 2010

Reference 46

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Observation cb7a150e-694e-49a4-92ae-8d0f3ed449e2 · outbound

This paper cites Drotár, J.

ROOFS: RObust biOmarker Feature Selection Drotár, J

Reference 47

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Observation 5e7955d1-d4b5-40ef-9984-6bd105e14bdb · outbound

This paper cites The schism study: Circulating cell-free dna size profiles as predictors of progression in advanced carcinoma treated with immune-checkpoint inhibitors.

ROOFS: RObust biOmarker Feature Selection The schism study: Circulating cell-free dna size profiles as predictors of progression in advanced carcinoma treated with immune-checkpoint inhibitors

Reference 48

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Observation 7ebba8b3-21cb-4126-ba48-d7deca586449 · outbound

This paper cites an unresolved cited work.

ROOFS: RObust biOmarker Feature Selection Unresolved cited work

Reference 49

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Observation bf321dea-8d82-4230-90ba-9637f17ac19e · outbound

This paper cites Schism: Mechanistic modeling of cfdna fragmen- tome dynamics predicts progression to immunotherapy, December 2025.

ROOFS: RObust biOmarker Feature Selection Schism: Mechanistic modeling of cfdna fragmen- tome dynamics predicts progression to immunotherapy, December 2025

Reference 50

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Observation 1ca7690c-41c1-4b77-848b-6f802233f5cc · outbound

This paper cites Block hsic lasso: model-free biomarker detection for ultra-high dimensional data.Bioinformatics (Oxford, England), 35(14): i427–i435, july 2019.

ROOFS: RObust biOmarker Feature Selection Block hsic lasso: model-free biomarker detection for ultra-high dimensional data.Bioinformatics (Oxford, England), 35(14): i427–i435, july 2019

Reference 51

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Observation cc94dfb1-2f06-452f-a435-bea3c3dc0b89 · outbound

This paper cites https://scikit-learn.org/stable/ auto_examples/inspection/plot_permutation_importance_multicollinear.html.

ROOFS: RObust biOmarker Feature Selection https://scikit-learn.org/stable/ auto_examples/inspection/plot_permutation_importance_multicollinear.html

Reference 52

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Observation cb67b710-8350-4fe3-a5d1-ed2f6506339b · outbound

This paper cites Gene selection for cancer classification using support vector machines.Machine Learning, 46:389–422, January 2002.

ROOFS: RObust biOmarker Feature Selection Gene selection for cancer classification using support vector machines.Machine Learning, 46:389–422, January 2002

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Observation 4d77771e-86d4-452e-b06f-eece7241a873 · outbound

This paper cites Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes.BMC Bioinformatics, 5(1):81, june 2004.

ROOFS: RObust biOmarker Feature Selection Joint analysis of two microarray gene-expression data sets to select lung adenocarcinoma marker genes.BMC Bioinformatics, 5(1):81, june 2004

Reference 54

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Observation 0f677710-f35f-4333-8fb8-6d4169df4b84 · outbound

This paper cites An iterative model-free feature screening procedure: Forward recursive selection.

ROOFS: RObust biOmarker Feature Selection An iterative model-free feature screening procedure: Forward recursive selection

Reference 55

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Observation 2ab97bff-2c56-4db4-89d4-bc3ba741d981 · outbound

This paper cites URL https://www.sciencedirect.com/science/ article/pii/S2001037024000692.

ROOFS: RObust biOmarker Feature Selection URL https://www.sciencedirect.com/science/ article/pii/S2001037024000692

Reference 370

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Observation 707eedf0-242f-4c1d-bb66-a7a8388c8738 · outbound

This paper cites doi: 10.1002/(SICI)1097-0258(19960229)15:4%3C361::AID-SIM168%3E3.0.CO;2-4.

ROOFS: RObust biOmarker Feature Selection doi: 10.1002/(SICI)1097-0258(19960229)15:4%3C361::AID-SIM168%3E3.0.CO;2-4

Reference 1996

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Observation f54dba18-a2b3-45a1-bd10-5abc698a71e7 · outbound

This paper cites doi: 10.1136/jitc-2022-005920.

ROOFS: RObust biOmarker Feature Selection doi: 10.1136/jitc-2022-005920

Reference 2023

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Observation 2811a086-d2bb-4080-9f1c-5cec460293e0 · outbound

This paper cites doi: 10.1038/s41598-025-16070-w.

ROOFS: RObust biOmarker Feature Selection doi: 10.1038/s41598-025-16070-w

Reference 2025

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Pith citing papers

Observation cd4f3159-c7bd-49d8-b94a-065f8f60b67a · inbound

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy cites this paper.

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy ROOFS: RObust biOmarker Feature Selection

Reference 4

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Observation 027a7ff5-2a53-40e8-a9e1-42791a3dfaeb · inbound

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy cites this paper.

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy ROOFS: RObust biOmarker Feature Selection

Reference 2026

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