Figure 3 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><i>TP53</i> gene mutation prediction from H&E images. <b>A,</b> Workflow for deep learning of <i>TP53</i> mutations from FN-RMS WSIs. <b>B</b> and <b>C,</b> Representative (<b>B</b>) H&E images and (<b>C&l...
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| _version_ | 1849927634567299072 |
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| 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 | 2025-11-25T12:41:14Z |
| dc.identifier.none.fl_str_mv | 10.1158/1078-0432.30705741 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Figure_3_from_Predicting_Molecular_Subtype_and_Survival_of_Rhabdomyosarcoma_Patients_Using_Deep_Learning_of_H_E_Images_A_Report_from_the_Children_s_Oncology_Group/30705741 |
| 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 3 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><i>TP53</i> gene mutation prediction from H&E images. <b>A,</b> Workflow for deep learning of <i>TP53</i> 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 TP53 wild-type tumor and a tumor with a TP53 p.P278T mutation (VAF = 0.474). <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> Performance statistics for <i>TP53</i> mutation prediction. <b>F,</b> Average ROC curve for <i>TP53</i> mutation prediction using holdout test data. <b>G,</b> Dot plot of <i>TP53</i> mutant samples (<i>n</i> = 15) showing relationship between <i>TP53</i> mutation VAF and A.I. positive prediction probability. Statistical analysis was performed using the Mann–Whitney <i>U</i> test.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_e866a29be56aeb30d45f1f7fe8c49282 |
| identifier_str_mv | 10.1158/1078-0432.30705741 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30705741 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY |
| spelling | Figure 3 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><i>TP53</i> gene mutation prediction from H&E images. <b>A,</b> Workflow for deep learning of <i>TP53</i> 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 TP53 wild-type tumor and a tumor with a TP53 p.P278T mutation (VAF = 0.474). <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> Performance statistics for <i>TP53</i> mutation prediction. <b>F,</b> Average ROC curve for <i>TP53</i> mutation prediction using holdout test data. <b>G,</b> Dot plot of <i>TP53</i> mutant samples (<i>n</i> = 15) showing relationship between <i>TP53</i> mutation VAF and A.I. positive prediction probability. Statistical analysis was performed using the Mann–Whitney <i>U</i> test.</p>2025-11-25T12:41:14ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1158/1078-0432.30705741https://figshare.com/articles/figure/Figure_3_from_Predicting_Molecular_Subtype_and_Survival_of_Rhabdomyosarcoma_Patients_Using_Deep_Learning_of_H_E_Images_A_Report_from_the_Children_s_Oncology_Group/30705741CC BYinfo:eu-repo/semantics/openAccessoai:figshare.com:article/307057412025-11-25T12:41:14Z |
| spellingShingle | Figure 3 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 3 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 3 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 3 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 3 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 3 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 3 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 |