| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.668 accuracy fraction · higher Uncertainty: 95% CI 0.661926535824708 to 0.674208294125555. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 31 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.814 auprc unitless · higher Uncertainty: 95% CI 0.807787931484189 to 0.820212932550006. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 27 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.715 auroc unitless · higher Uncertainty: 95% CI 0.70710749844872 to 0.722442127087171. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 26 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.712 f1-score fraction · higher Uncertainty: 95% CI 0.705971494993182 to 0.719210768411687. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 30 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.662 recall fraction · higher Uncertainty: 95% CI 0.650750739357206 to 0.67133671734573. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 28 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction 0 to 0.03 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.679 specificity fraction · higher Uncertainty: 95% CI 0.664012191060481 to 0.693007440108115. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction 0 to 0.03 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-0-3pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 29 (feat 'C/T', ichorcna_strat '[0, 0.03]', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.725 accuracy fraction · higher Uncertainty: 95% CI 0.717657590759076 to 0.731485633857503. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 67 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.676 auprc unitless · higher Uncertainty: 95% CI 0.662511511954401 to 0.687286467204416. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 63 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.74 auroc unitless · higher Uncertainty: 95% CI 0.729750718606295 to 0.749105498448642. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 62 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.586 f1-score fraction · higher Uncertainty: 95% CI 0.573653996289792 to 0.598196337482905. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 66 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.551 recall fraction · higher Uncertainty: 95% CI 0.530124005366327 to 0.571378052986039. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 64 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.03 to 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.822 specificity fraction · higher Uncertainty: 95% CI 0.809713939029489 to 0.834367044365908. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.03 to 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-3-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 65 (feat 'C/T', ichorcna_strat '(0.03, 0.1]', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.694 accuracy fraction · higher Uncertainty: 95% CI 0.687577912513444 to 0.700234945319011. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 139 (feat 'C/T', ichorcna_strat 'all', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.892 auprc unitless · higher Uncertainty: 95% CI 0.889336323734103 to 0.895541264100089. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 135 (feat 'C/T', ichorcna_strat 'all', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.744 auroc unitless · higher Uncertainty: 95% CI 0.738865828424514 to 0.748450223017611. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 134 (feat 'C/T', ichorcna_strat 'all', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.771 f1-score fraction · higher Uncertainty: 95% CI 0.764739366896192 to 0.778687054765388. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 138 (feat 'C/T', ichorcna_strat 'all', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.704 recall fraction · higher Uncertainty: 95% CI 0.690319607682921 to 0.71806166813913. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 136 (feat 'C/T', ichorcna_strat 'all', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with all tumour fractions vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.667 specificity fraction · higher Uncertainty: 95% CI 0.647183554832278 to 0.684332031420548. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), all tumour fractions ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-all Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 137 (feat 'C/T', ichorcna_strat 'all', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.776 accuracy fraction · higher Uncertainty: 95% CI 0.765470857002953 to 0.784642209407189. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 103 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.785 auprc unitless · higher Uncertainty: 95% CI 0.769836107735504 to 0.800076799971187. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 99 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.849 auroc unitless · higher Uncertainty: 95% CI 0.840539612603239 to 0.857740129706982. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 98 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.69 f1-score fraction · higher Uncertainty: 95% CI 0.675353278554447 to 0.702932669971401. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 102 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.669 recall fraction · higher Uncertainty: 95% CI 0.652207297603603 to 0.686356362063859. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 100 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, 5' C/T motif ratio per bin (C/T) (Wang et al. 2026) | Protocol: UNITE cross-validation, cancers with ichorCNA tumour fraction above 0.1 vs healthy (Wang et al. 2026)
Dataset: UNITE cross-validation set: shallow WGS plasma cfDNA, 458 healthy and 1,232 cancer samples | 0.84 specificity fraction · higher Uncertainty: 95% CI 0.829078704222703 to 0.851051048623063. Interval over the 50 outer test folds as printed in columns G and H Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceUNITE XGBoost 5' C/T motif ratio per bin (C/T), ichorCNA tumour fraction above 0.1 ctdnafrag-20261009-protocol-wang2026-unite-cv-tf-over-10pct Aggregation: Not reported A scalable deep-learning framework for cancer detection using cell-free DNA shallow whole-genome sequencing; Wang et al. 2026, Data file S2 (model scores and summary statistics) · Data file S2 sheet STATS_xgb_x1-x6, row 101 (feat 'C/T', ichorcna_strat '(0.1, 1]', .metric 'Specificity'), column D 'mean' |
|---|