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TCGA-PAAD

Last updated 2026-02-04 16:27 · Cached 2026-02-08 16:59

Features Inference Manifest Tiling Training

Stage Summary Pipeline status at a glance Pipeline

Features
Encoders detected: gigapath_ft (209 files, 181 with labels), h-optimus-0 (209 files, 181 with labels), prov-gigapath (209 files, 181 with labels), uni (209 files, 181 with labels), virchow (209 files, 181 with labels), virchow2 (209 files, 181 with labels)
Inference
265 prediction(s) · 200 positive label(s) · dataset tcga
Manifest
181 rows, 13 columns
Tiling
Tiling manifest covers 209 case(s), 181 with labels
Training
90 training run(s)

Case Summary Track cohort coverage by encoder Cohort

Cases Inspect case-level tiles and encoders Cases

Manifest Overview Preview the manifest and target distribution Manifest

Download CSV

181 rows · 9 columns

Target: KRAS_BINARY Target: KRAS

slide_id	KRAS_binary	DMP_ASSAY_ID	split_1	split_2	split_3	split_4	split_5	KRAS
TCGA-2J-AAB1_TCGA-2J-AAB1-01Z-00-DX1	1	TCGA-2J-AAB1_TCGA-2J-AAB1-01Z-00-DX1	test	train	train	train	train	Positive
TCGA-2J-AAB4_TCGA-2J-AAB4-01Z-00-DX1	1	TCGA-2J-AAB4_TCGA-2J-AAB4-01Z-00-DX1	train	train	train	test	train	Positive
TCGA-2J-AAB6_TCGA-2J-AAB6-01Z-00-DX1	1	TCGA-2J-AAB6_TCGA-2J-AAB6-01Z-00-DX1	test	train	test	train	test	Positive
TCGA-2J-AAB8_TCGA-2J-AAB8-01Z-00-DX1	1	TCGA-2J-AAB8_TCGA-2J-AAB8-01Z-00-DX1	test	train	train	train	train	Positive
TCGA-2J-AAB9_TCGA-2J-AAB9-01Z-00-DX1	1	TCGA-2J-AAB9_TCGA-2J-AAB9-01Z-00-DX1	test	train	train	train	train	Positive

Cross-Validation Performance Compare experiments across validation splits Validation

Training Runs Artifacts and metrics for each experiment Experiments

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Model	Target	Aggregator	Split	Epoch 200	Macro AUC	Macro BER	Macro FPR	Macro FNR	Artifact
uni	KRAS	GMA PUB	split_1	120	0.7262228260869565	0.3763586956521739	0.6875	0.0652173913043478	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_3	120	0.6983695652173914	0.4198369565217391	0.6875	0.1521739130434782	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_1	120	0.6243206521739131	0.3980978260869565	0.6875	0.108695652173913	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_3	120	0.6752717391304348	0.5027173913043478	0.875	0.1304347826086956	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_2	120	0.6411347517730497	0.3624113475177305	0.5333333333333333	0.1914893617021276	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_4	120	0.743161094224924	0.3632218844984802	0.4285714285714285	0.2978723404255319	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_2	120	0.6453900709219857	0.3638297872340425	0.6	0.1276595744680851	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_5	120	0.7594202898550724	0.2652173913043478	0.4	0.1304347826086956	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_3	120	0.6263586956521738	0.3790760869565217	0.5625	0.1956521739130435	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_4	120	0.7857142857142856	0.2955927051671733	0.3571428571428571	0.2340425531914893	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_3	120	0.579483695652174	0.4714673913043478	0.8125	0.1304347826086956	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_2	120	0.7106382978723405	0.3198581560283688	0.5333333333333333	0.1063829787234042	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_2	120	0.6865248226950355	0.3957446808510638	0.6	0.1914893617021276	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_4	120	0.7074468085106383	0.2993920972644376	0.4285714285714285	0.1702127659574468	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_1	120	0.8464673913043478	0.2839673913043478	0.4375	0.1304347826086956	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_2	120	0.7106382978723405	0.3198581560283688	0.5333333333333333	0.1063829787234042	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_3	120	0.579483695652174	0.4714673913043478	0.8125	0.1304347826086956	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_2	120	0.6453900709219857	0.3638297872340425	0.6	0.1276595744680851	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_4	120	0.7857142857142856	0.2955927051671733	0.3571428571428571	0.2340425531914893	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_1	120	0.8464673913043478	0.2839673913043478	0.4375	0.1304347826086956	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_3	120	0.6779891304347826	0.4605978260869565	0.8125	0.108695652173913	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_1	120	0.7323369565217391	0.4701086956521739	0.875	0.0652173913043478	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_5	120	0.7528985507246376	0.2992753623188405	0.5333333333333333	0.0652173913043478	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_4	120	0.756838905775076	0.2993920972644376	0.4285714285714285	0.1702127659574468	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_1	120	0.7323369565217391	0.4701086956521739	0.875	0.0652173913043478	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_3	120	0.6263586956521738	0.3790760869565217	0.5625	0.1956521739130435	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_5	120	0.6731884057971014	0.4210144927536232	0.7333333333333333	0.108695652173913	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_3	120	0.6752717391304348	0.5027173913043478	0.875	0.1304347826086956	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_5	120	0.6304347826086956	0.3543478260869565	0.6	0.108695652173913	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_5	120	0.8579710144927537	0.2543478260869565	0.4	0.108695652173913	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_2	120	0.6340425531914894	0.474468085106383	0.8	0.1489361702127659	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_4	120	0.7074468085106383	0.2993920972644376	0.4285714285714285	0.1702127659574468	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_3	120	0.6800271739130435	0.4402173913043478	0.75	0.1304347826086956	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_4	120	0.8130699088145896	0.2424012158054711	0.3571428571428571	0.1276595744680851	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_5	120	0.7594202898550724	0.2652173913043478	0.4	0.1304347826086956	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_4	120	0.7948328267477204	0.3100303951367781	0.4285714285714285	0.1914893617021276	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_1	120	0.6005434782608696	0.4402173913043478	0.75	0.1304347826086956	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_1	120	0.6005434782608696	0.4402173913043478	0.75	0.1304347826086956	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_1	120	0.6243206521739131	0.3980978260869565	0.6875	0.108695652173913	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_2	120	0.7056737588652482	0.4092198581560283	0.7333333333333333	0.0851063829787234	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_3	120	0.6779891304347826	0.4605978260869565	0.8125	0.108695652173913	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_4	120	0.7948328267477204	0.3100303951367781	0.4285714285714285	0.1914893617021276	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_5	120	0.8579710144927537	0.2543478260869565	0.4	0.108695652173913	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_3	120	0.6983695652173914	0.4198369565217391	0.6875	0.1521739130434782	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_5	120	0.7253623188405798	0.3434782608695652	0.6	0.0869565217391304	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_4	120	0.8130699088145896	0.2424012158054711	0.3571428571428571	0.1276595744680851	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_1	120	0.6372282608695652	0.4184782608695652	0.75	0.0869565217391304	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_2	120	0.6340425531914894	0.474468085106383	0.8	0.1489361702127659	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_2	120	0.6411347517730497	0.3624113475177305	0.5333333333333333	0.1914893617021276	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_3	120	0.6800271739130435	0.4402173913043478	0.75	0.1304347826086956	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_4	120	0.743161094224924	0.3632218844984802	0.4285714285714285	0.2978723404255319	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_1	120	0.7262228260869565	0.3763586956521739	0.6875	0.0652173913043478	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_4	120	0.756838905775076	0.2993920972644376	0.4285714285714285	0.1702127659574468	`cumulative_results.csv`
virchow	KRAS	GMA PUB	split_5	120	0.7253623188405798	0.3434782608695652	0.6	0.0869565217391304	`cumulative_results.csv`
uni	KRAS	GMA PUB	split_5	120	0.6304347826086956	0.3543478260869565	0.6	0.108695652173913	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_5	120	0.7528985507246376	0.2992753623188405	0.5333333333333333	0.0652173913043478	`cumulative_results.csv`
virchow2	KRAS	GMA PUB	split_2	120	0.6865248226950355	0.3957446808510638	0.6	0.1914893617021276	`cumulative_results.csv`
gigapath_ft	KRAS	GMA PUB	split_2	120	0.7056737588652482	0.4092198581560283	0.7333333333333333	0.0851063829787234	`cumulative_results.csv`
h-optimus-0	KRAS	GMA PUB	split_1	120	0.6372282608695652	0.4184782608695652	0.75	0.0869565217391304	`cumulative_results.csv`
prov-gigapath	KRAS	GMA PUB	split_5	120	0.6731884057971014	0.4210144927536232	0.7333333333333333	0.108695652173913	`cumulative_results.csv`

External Inference Diagnostics Interactive ROC/PR curves for each external inference experiment Inference