| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.73 accuracy fraction · higher Uncertainty: Not reported by the source Coverage: 499 cancer patients scored (n printed in cell B10) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E10; Discovery block; row 'All cancer'; column 'GCNN' under 'All stage' (n in B10) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.87 recall fraction · higher Uncertainty: Not reported by the source Coverage: 156 cancer patients scored (n printed in cell B5) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E5; Discovery block; row 'Breast'; column 'GCNN' under 'All stage' (n in B5) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.71 recall fraction · higher Uncertainty: Not reported by the source Coverage: 106 cancer patients scored (n printed in cell B6) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E6; Discovery block; row 'CRC'; column 'GCNN' under 'All stage' (n in B6) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.55 recall fraction · higher Uncertainty: Not reported by the source Coverage: 11 cancer patients scored (n printed in cell F6) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', I6; Discovery block; row 'CRC'; column 'GCNN' under 'Stage I' (n in F6) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.72 recall fraction · higher Uncertainty: Not reported by the source Coverage: 41 cancer patients scored (n printed in cell J6) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', M6; Discovery block; row 'CRC'; column 'GCNN' under 'Stage II' (n in J6) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.71 recall fraction · higher Uncertainty: Not reported by the source Coverage: 41 cancer patients scored (n printed in cell N6) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', Q6; Discovery block; row 'CRC'; column 'GCNN' under 'Stage III' (n in N6) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.77 recall fraction · higher Uncertainty: Not reported by the source Coverage: 13 cancer patients scored (n printed in cell R6) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', U6; Discovery block; row 'CRC'; column 'GCNN' under 'Non-metastasis with unknown stage' (n in R6) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.54 recall fraction · higher Uncertainty: Not reported by the source Coverage: 67 cancer patients scored (n printed in cell B7) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E7; Discovery block; row 'Gastric'; column 'GCNN' under 'All stage' (n in B7) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.5 recall fraction · higher Uncertainty: Not reported by the source Coverage: 4 cancer patients scored (n printed in cell F7) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', I7; Discovery block; row 'Gastric'; column 'GCNN' under 'Stage I' (n in F7) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.58 recall fraction · higher Uncertainty: Not reported by the source Coverage: 12 cancer patients scored (n printed in cell J7) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', M7; Discovery block; row 'Gastric'; column 'GCNN' under 'Stage II' (n in J7) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.65 recall fraction · higher Uncertainty: Not reported by the source Coverage: 23 cancer patients scored (n printed in cell N7) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', Q7; Discovery block; row 'Gastric'; column 'GCNN' under 'Stage III' (n in N7) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.43 recall fraction · higher Uncertainty: Not reported by the source Coverage: 28 cancer patients scored (n printed in cell R7) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', U7; Discovery block; row 'Gastric'; column 'GCNN' under 'Non-metastasis with unknown stage' (n in R7) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.82 recall fraction · higher Uncertainty: Not reported by the source Coverage: 77 cancer patients scored (n printed in cell B8) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E8; Discovery block; row 'Liver'; column 'GCNN' under 'All stage' (n in B8) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 1 recall fraction · higher Uncertainty: Not reported by the source Coverage: 4 cancer patients scored (n printed in cell F8) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', I8; Discovery block; row 'Liver'; column 'GCNN' under 'Stage I' (n in F8) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.76 recall fraction · higher Uncertainty: Not reported by the source Coverage: 21 cancer patients scored (n printed in cell J8) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', M8; Discovery block; row 'Liver'; column 'GCNN' under 'Stage II' (n in J8) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 1 recall fraction · higher Uncertainty: Not reported by the source Coverage: 12 cancer patients scored (n printed in cell N8) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', Q8; Discovery block; row 'Liver'; column 'GCNN' under 'Stage III' (n in N8) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.78 recall fraction · higher Uncertainty: Not reported by the source Coverage: 40 cancer patients scored (n printed in cell R8) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', U8; Discovery block; row 'Liver'; column 'GCNN' under 'Non-metastasis with unknown stage' (n in R8) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.59 recall fraction · higher Uncertainty: Not reported by the source Coverage: 93 cancer patients scored (n printed in cell B9) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E9; Discovery block; row 'Lung'; column 'GCNN' under 'All stage' (n in B9) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.5 recall fraction · higher Uncertainty: Not reported by the source Coverage: 2 cancer patients scored (n printed in cell F9) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', I9; Discovery block; row 'Lung'; column 'GCNN' under 'Stage I' (n in F9) |
|---|
| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.37 recall fraction · higher Uncertainty: Not reported by the source Coverage: 11 cancer patients scored (n printed in cell J9) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', M9; Discovery block; row 'Lung'; column 'GCNN' under 'Stage II' (n in J9) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.6 recall fraction · higher Uncertainty: Not reported by the source Coverage: 47 cancer patients scored (n printed in cell N9) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', Q9; Discovery block; row 'Lung'; column 'GCNN' under 'Stage III' (n in N9) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, discovery cohort 10-fold cross-validation
Dataset: SPOT-MAS discovery cohort, 499 non-metastatic cancer patients (five cancer types) | 0.67 recall fraction · higher Uncertainty: Not reported by the source Coverage: 33 cancer patients scored (n printed in cell R9) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (discovery) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-discovery-cv Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', U9; Discovery block; row 'Lung'; column 'GCNN' under 'Non-metastasis with unknown stage' (n in R9) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, independent validation cohort
Dataset: SPOT-MAS validation cohort, 239 non-metastatic cancer patients (five cancer types) | 0.69 accuracy fraction · higher Uncertainty: Not reported by the source Coverage: 239 cancer patients scored (n printed in cell B19) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (validation) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-validation Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E19; Validation block; row 'All cancer'; column 'GCNN' under 'All stage' (n in B19) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, independent validation cohort
Dataset: SPOT-MAS validation cohort, 239 non-metastatic cancer patients (five cancer types) | 0.78 recall fraction · higher Uncertainty: Not reported by the source Coverage: 67 cancer patients scored (n printed in cell B14) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (validation) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-validation Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E14; Validation block; row 'Breast'; column 'GCNN' under 'All stage' (n in B14) |
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| Configuration: SPOT-MAS tissue-of-origin Graph convolutional neural network (GCNN) | Protocol: SPOT-MAS five-class tissue of origin, independent validation cohort
Dataset: SPOT-MAS validation cohort, 239 non-metastatic cancer patients (five cancer types) | 0.66 recall fraction · higher Uncertainty: Not reported by the source Coverage: 53 cancer patients scored (n printed in cell B15) | Author-reported evaluation · Source checkedMethods, coverage and sourceSPOT-MAS tissue of origin, GCNN (validation) ctdnameth-20261009-protocol-nguyen2023-spotmas-too-validation Aggregation: Not reported Multimodal analysis of methylomics and fragmentomics in plasma cell-free DNA for multi-cancer early detection and localization; Nguyen et al. 2023, Supplementary file 1 (Tables S1-S11) · Supplementary file 1, sheet 'Table S9', E15; Validation block; row 'CRC'; column 'GCNN' under 'All stage' (n in B15) |
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