{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/uncertainty-informed-deep-learning-models","title":"Uncertainty-Informed Deep Learning Models Enable High-Confidence Predictions for Digital Histopathology","arxiv_id":"2204.04516","date":"2022-04-09","proceeding":null,"authors":["James M Dolezal","Andrew Srisuwananukorn","Dmitry Karpeyev","Siddhi Ramesh","Sara Kochanny","Brittany Cody","Aaron Mansfield","Sagar Rakshit","Radhika Bansa","Melanie Bois","Aaron O Bungum","Jefree J Schulte","Everett E Vokes","Marina Chiara Garassino","Aliya N Husain","Alexander T Pearson"],"abstract":"A model's ability to express its own predictive uncertainty is an essential attribute for maintaining clinical user confidence as computational biomarkers are deployed into real-world medical settings. In the domain of cancer digital histopathology, we describe a novel, clinically-oriented approach to uncertainty quantification (UQ) for whole-slide images, estimating uncertainty using dropout and calculating thresholds on training data to establish cutoffs for low- and high-confidence predictions. We train models to identify lung adenocarcinoma vs. squamous cell carcinoma and show that high-confidence predictions outperform predictions without UQ, in both cross-validation and testing on two large external datasets spanning multiple institutions. Our testing strategy closely approximates real-world application, with predictions generated on unsupervised, unannotated slides using predetermined thresholds. Furthermore, we show that UQ thresholding remains reliable in the setting of domain shift, with accurate high-confidence predictions of adenocarcinoma vs. squamous cell carcinoma for out-of-distribution, non-lung cancer cohorts.","url_abs":"https://arxiv.org/abs/2204.04516v1","url_pdf":"https://arxiv.org/pdf/2204.04516v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"uncertainty-informed-deep-learning-models","repo_url":"https://github.com/jamesdolezal/biscuit","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"uncertainty-informed-deep-learning-models","repo_url":"https://github.com/jamesdolezal/slideflow","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"attribute","task_name":"Attribute"},{"task_slug":"uncertainty-quantification","task_name":"Uncertainty Quantification"},{"task_slug":"whole-slide-images","task_name":"whole slide images"}],"methods":[{"method_slug":"1x1-convolution","method_name":"1x1 Convolution"},{"method_slug":"average-pooling","method_name":"Average Pooling"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"depthwise-convolution","method_name":"Depthwise Convolution"},{"method_slug":"depthwise-separable-convolution","method_name":"Depthwise Separable Convolution"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"global-average-pooling","method_name":"Global Average Pooling"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"pointwise-convolution","method_name":"Pointwise Convolution"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2204.04516","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2204.04516"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jamesdolezal/biscuit","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/jamesdolezal/slideflow","reach":{"status":"ok","spdx":"Apache-2.0"}}],"summary":{"unverified":11},"by_repo_kind":{"official":{"samples":11,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"383daf686e96763a","entry":"batch_loss_crossentropy","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/tensorflow_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/tensorflow_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"383daf686e96763a"}},{"code_sha256_prefix":"15f7d45767c330f3","entry":"calculate_heatmap_extent","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/heatmap.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/heatmap.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"15f7d45767c330f3"}},{"code_sha256_prefix":"7d98ff8e54bdaca6","entry":"convert_dataset","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/adv_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/adv_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7d98ff8e54bdaca6"}},{"code_sha256_prefix":"84b9fad938f056de","entry":"get_layer_index_by_name","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/tensorflow_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/tensorflow_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"84b9fad938f056de"}},{"code_sha256_prefix":"09dddb2a3dd86eec","entry":"get_module_by_name","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/torch_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/torch_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"09dddb2a3dd86eec"}},{"code_sha256_prefix":"61499d2ec0c1fa05","entry":"get_uq_predictions","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/torch_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/torch_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"61499d2ec0c1fa05"}},{"code_sha256_prefix":"db044050ec123a2d","entry":"negative_log_likelihood","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/tensorflow_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/tensorflow_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"db044050ec123a2d"}},{"code_sha256_prefix":"4b76772761f0cc1a","entry":"print_module_summary","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/model/torch_utils.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/model/torch_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4b76772761f0cc1a"}},{"code_sha256_prefix":"c55cafde08716f01","entry":"register_vcs_handler","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/_version.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/_version.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"c55cafde08716f01"}},{"code_sha256_prefix":"dbb37355631dabcf","entry":"run_command","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/_version.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/_version.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"dbb37355631dabcf"}},{"code_sha256_prefix":"5032e3b81c0fffb3","entry":"versions_from_parentdir","repo":"jamesdolezal/slideflow","repo_kind":"official","path":"slideflow/_version.py","file_url":"https://github.com/jamesdolezal/slideflow/blob/HEAD/slideflow/_version.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"5032e3b81c0fffb3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}