Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group
<p>Prediction of RAS pathway mutations using a trained CNN. <b>A,</b> Workflow for deep learning of RAS pathway mutations from FN-RMS WSIs. <b>B</b> and <b>C,</b> Representative (<b>B</b>) H&E images and (<b>C</b>) class activatio...
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| _version_ | 1849927634569396224 |
|---|---|
| author | David Milewski (15050643) |
| author2 | Hyun Jung (15050646) G. Thomas Brown (15050649) Yanling Liu (15050652) Ben Somerville (15050655) Curtis Lisle (15050658) Marc Ladanyi (15050661) Erin R. Rudzinski (15050664) Hyoyoung Choo-Wosoba (15050667) Donald A. Barkauskas (15050670) Tammy Lo (15050673) David Hall (15050676) Corinne M. Linardic (15050679) Jun S. Wei (14955721) Hsien-Chao Chou (14955718) Stephen X. Skapek (15050682) Rajkumar Venkatramani (15050685) Peter K. Bode (15050688) Seth M. Steinberg (15043179) George Zaki (15050691) Igor B. Kuznetsov (15050694) Douglas S. Hawkins (15050697) Jack F. Shern (14938001) Jack Collins (15050700) Javed Khan (15046967) |
| author2_role | author author author author author author author author author author author author author author author author author author author author author author author author |
| author_facet | David Milewski (15050643) Hyun Jung (15050646) G. Thomas Brown (15050649) Yanling Liu (15050652) Ben Somerville (15050655) Curtis Lisle (15050658) Marc Ladanyi (15050661) Erin R. Rudzinski (15050664) Hyoyoung Choo-Wosoba (15050667) Donald A. Barkauskas (15050670) Tammy Lo (15050673) David Hall (15050676) Corinne M. Linardic (15050679) Jun S. Wei (14955721) Hsien-Chao Chou (14955718) Stephen X. Skapek (15050682) Rajkumar Venkatramani (15050685) Peter K. Bode (15050688) Seth M. Steinberg (15043179) George Zaki (15050691) Igor B. Kuznetsov (15050694) Douglas S. Hawkins (15050697) Jack F. Shern (14938001) Jack Collins (15050700) Javed Khan (15046967) |
| author_role | author |
| dc.creator.none.fl_str_mv | David Milewski (15050643) Hyun Jung (15050646) G. Thomas Brown (15050649) Yanling Liu (15050652) Ben Somerville (15050655) Curtis Lisle (15050658) Marc Ladanyi (15050661) Erin R. Rudzinski (15050664) Hyoyoung Choo-Wosoba (15050667) Donald A. Barkauskas (15050670) Tammy Lo (15050673) David Hall (15050676) Corinne M. Linardic (15050679) Jun S. Wei (14955721) Hsien-Chao Chou (14955718) Stephen X. Skapek (15050682) Rajkumar Venkatramani (15050685) Peter K. Bode (15050688) Seth M. Steinberg (15043179) George Zaki (15050691) Igor B. Kuznetsov (15050694) Douglas S. Hawkins (15050697) Jack F. Shern (14938001) Jack Collins (15050700) Javed Khan (15046967) |
| dc.date.none.fl_str_mv | 2025-11-25T12:41:12Z |
| dc.identifier.none.fl_str_mv | 10.1158/1078-0432.30705738 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Figure_4_from_Predicting_Molecular_Subtype_and_Survival_of_Rhabdomyosarcoma_Patients_Using_Deep_Learning_of_H_E_Images_A_Report_from_the_Children_s_Oncology_Group/30705738 |
| dc.rights.none.fl_str_mv | CC BY info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Cancer Cancer Detection and Diagnosis Methods and Technology Biomarkers Prognostic biomarkers Computational Methods Artificial intelligence & machine learning Pediatric Cancers Sarcomas Soft-tissue sarcoma |
| dc.title.none.fl_str_mv | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Prediction of RAS pathway mutations using a trained CNN. <b>A,</b> Workflow for deep learning of RAS pathway mutations from FN-RMS WSIs. <b>B</b> and <b>C,</b> Representative (<b>B</b>) H&E images and (<b>C</b>) class activation maps of a RAS pathway wild-type tumor and a tumor with a KRAS p.G12C mutation (VAF = 0.659). <b>D,</b> Confusion matrix for predictions on a test dataset. Micro F1, Macro F1, and Matthew's correlation coefficient shown below. <b>E,</b> Statistics for confusion matrix. <b>F,</b> Average ROC curve from holdout test data.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_cb2eeaae14f8fbf46b5f7546eae5e9e0 |
| identifier_str_mv | 10.1158/1078-0432.30705738 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30705738 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY |
| spelling | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology GroupDavid Milewski (15050643)Hyun Jung (15050646)G. Thomas Brown (15050649)Yanling Liu (15050652)Ben Somerville (15050655)Curtis Lisle (15050658)Marc Ladanyi (15050661)Erin R. Rudzinski (15050664)Hyoyoung Choo-Wosoba (15050667)Donald A. Barkauskas (15050670)Tammy Lo (15050673)David Hall (15050676)Corinne M. Linardic (15050679)Jun S. Wei (14955721)Hsien-Chao Chou (14955718)Stephen X. Skapek (15050682)Rajkumar Venkatramani (15050685)Peter K. Bode (15050688)Seth M. Steinberg (15043179)George Zaki (15050691)Igor B. Kuznetsov (15050694)Douglas S. Hawkins (15050697)Jack F. Shern (14938001)Jack Collins (15050700)Javed Khan (15046967)CancerCancer Detection and DiagnosisMethods and TechnologyBiomarkersPrognostic biomarkersComputational MethodsArtificial intelligence & machine learningPediatric CancersSarcomasSoft-tissue sarcoma<p>Prediction of RAS pathway mutations using a trained CNN. <b>A,</b> Workflow for deep learning of RAS pathway mutations from FN-RMS WSIs. <b>B</b> and <b>C,</b> Representative (<b>B</b>) H&E images and (<b>C</b>) class activation maps of a RAS pathway wild-type tumor and a tumor with a KRAS p.G12C mutation (VAF = 0.659). <b>D,</b> Confusion matrix for predictions on a test dataset. Micro F1, Macro F1, and Matthew's correlation coefficient shown below. <b>E,</b> Statistics for confusion matrix. <b>F,</b> Average ROC curve from holdout test data.</p>2025-11-25T12:41:12ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1158/1078-0432.30705738https://figshare.com/articles/figure/Figure_4_from_Predicting_Molecular_Subtype_and_Survival_of_Rhabdomyosarcoma_Patients_Using_Deep_Learning_of_H_E_Images_A_Report_from_the_Children_s_Oncology_Group/30705738CC BYinfo:eu-repo/semantics/openAccessoai:figshare.com:article/307057382025-11-25T12:41:12Z |
| spellingShingle | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group David Milewski (15050643) Cancer Cancer Detection and Diagnosis Methods and Technology Biomarkers Prognostic biomarkers Computational Methods Artificial intelligence & machine learning Pediatric Cancers Sarcomas Soft-tissue sarcoma |
| status_str | publishedVersion |
| title | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| title_full | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| title_fullStr | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| title_full_unstemmed | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| title_short | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| title_sort | Figure 4 from Predicting Molecular Subtype and Survival of Rhabdomyosarcoma Patients Using Deep Learning of H&E Images: A Report from the Children's Oncology Group |
| topic | Cancer Cancer Detection and Diagnosis Methods and Technology Biomarkers Prognostic biomarkers Computational Methods Artificial intelligence & machine learning Pediatric Cancers Sarcomas Soft-tissue sarcoma |