| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.808 accuracy fraction · higher Uncertainty: 95% CI 0.802240119639737 to 0.814043033337814. 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 All five feature types (UNITE-XGB, model X6), 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 7 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.922 auprc unitless · higher Uncertainty: 95% CI 0.916937208671138 to 0.926555712665032. 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 All five feature types (UNITE-XGB, model X6), 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 3 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.878 auroc unitless · higher Uncertainty: 95% CI 0.871088518357102 to 0.884027033099431. 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 All five feature types (UNITE-XGB, model X6), 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 2 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.845 f1-score fraction · higher Uncertainty: 95% CI 0.839539847060346 to 0.850016168231015. 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 All five feature types (UNITE-XGB, model X6), 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 6 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.841 recall fraction · higher Uncertainty: 95% CI 0.832242583740728 to 0.848880621293709. 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 All five feature types (UNITE-XGB, model X6), 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 4 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.754 specificity fraction · higher Uncertainty: 95% CI 0.742458347688347 to 0.764656413577121. 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 All five feature types (UNITE-XGB, model X6), 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 5 (feat 'All', ichorcna_strat '[0, 0.03]', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.922 accuracy fraction · higher Uncertainty: 95% CI 0.915937876140555 to 0.927509270044652. 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 All five feature types (UNITE-XGB, model X6), 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 43 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.952 auprc unitless · higher Uncertainty: 95% CI 0.946540275378965 to 0.957277248648428. 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 All five feature types (UNITE-XGB, model X6), 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 39 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.962 auroc unitless · higher Uncertainty: 95% CI 0.956864305379267 to 0.965835559427218. 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 All five feature types (UNITE-XGB, model X6), 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 38 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.886 f1-score fraction · higher Uncertainty: 95% CI 0.876606186107664 to 0.894600007080721. 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 All five feature types (UNITE-XGB, model X6), 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 42 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.85 recall fraction · higher Uncertainty: 95% CI 0.835385112660256 to 0.863737766561006. 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 All five feature types (UNITE-XGB, model X6), 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 40 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.962 specificity fraction · higher Uncertainty: 95% CI 0.956435237452299 to 0.968120572709345. 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 All five feature types (UNITE-XGB, model X6), 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 41 (feat 'All', ichorcna_strat '(0.03, 0.1]', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.852 accuracy fraction · higher Uncertainty: 95% CI 0.847567448340331 to 0.857161440034147. 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 All five feature types (UNITE-XGB, model X6), 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 115 (feat 'All', ichorcna_strat 'all', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.97 auprc unitless · higher Uncertainty: 95% CI 0.968264347567679 to 0.971522552495379. 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 All five feature types (UNITE-XGB, model X6), 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 111 (feat 'All', ichorcna_strat 'all', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.916 auroc unitless · higher Uncertainty: 95% CI 0.912077380234279 to 0.919242513352284. 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 All five feature types (UNITE-XGB, model X6), 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 110 (feat 'All', ichorcna_strat 'all', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.898 f1-score fraction · higher Uncertainty: 95% CI 0.894147470612093 to 0.901005064645811. 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 All five feature types (UNITE-XGB, model X6), 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 114 (feat 'All', ichorcna_strat 'all', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.879 recall fraction · higher Uncertainty: 95% CI 0.872041210173299 to 0.885717327526083. 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 All five feature types (UNITE-XGB, model X6), 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 112 (feat 'All', ichorcna_strat 'all', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.779 specificity fraction · higher Uncertainty: 95% CI 0.767944094467296 to 0.791742927566671. 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 All five feature types (UNITE-XGB, model X6), 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 113 (feat 'All', ichorcna_strat 'all', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.984 accuracy fraction · higher Uncertainty: 95% CI 0.98116327437065 to 0.987107461013067. 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 All five feature types (UNITE-XGB, model X6), 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 79 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'Accuracy'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.997 auprc unitless · higher Uncertainty: 95% CI 0.996006106960816 to 0.998084845479669. 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 All five feature types (UNITE-XGB, model X6), 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 75 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'AUPRC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.998 auroc unitless · higher Uncertainty: 95% CI 0.997098449739814 to 0.99862092981655. 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 All five feature types (UNITE-XGB, model X6), 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 74 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'AUROC'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.978 f1-score fraction · higher Uncertainty: 95% CI 0.974268340402816 to 0.98223292480869. 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 All five feature types (UNITE-XGB, model X6), 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 78 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'F1'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.964 recall fraction · higher Uncertainty: 95% CI 0.956687062702704 to 0.971843551863538. 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 All five feature types (UNITE-XGB, model X6), 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 76 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'Sensitivity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, All five feature types (UNITE-XGB, model X6) (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 | 0.996 specificity fraction · higher Uncertainty: 95% CI 0.993627598409234 to 0.998498620004266. 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 All five feature types (UNITE-XGB, model X6), 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 77 (feat 'All', ichorcna_strat '(0.1, 1]', .metric 'Specificity'), column D 'mean' |
|---|
| Configuration: UNITE XGBoost, Copy number aberration (CNA) (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 | 0.686 accuracy fraction · higher Uncertainty: 95% CI 0.677782380024197 to 0.693932114531523. 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 Copy number aberration (CNA), 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 25 (feat 'CNV', ichorcna_strat '[0, 0.03]', .metric 'Accuracy'), column D 'mean' |
|---|