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Progress in this field has been limited by the scarcity of large, diverse, and well\u2010validated whole slide image (WSI) datasets. To address this gap, HISTAI introduced an open\u2010source resource comprising over 112,000 WSIs across multiple organ systems with associated clinical metadata. Here, we present a pathologist\u2010led evaluation of label accuracy, metadata completeness, and dataset composition across 328 selected cases from this resource. Although HISTAI reports 47,279 cases, we identified only 44,564 unique cases after accounting for missing entries and duplicate records. Basic demographic information, including age and sex, was available for only 55% of cases. Dataset composition was uneven, with dermatopathology accounting for 47.1% of cases and gastrointestinal pathology for 24.0%; however, primary specialty was explicitly reported for only 39.6% of cases, obscuring this imbalance within the provided metadata. Notably, clinical ground truth is recorded in the Conclusion column. Concordance between the dataset's Conclusion and Diagnosis fields was observed in only 20.7% of cases, while 27.1% contained conflicting diagnoses. In a focused review of 198 cases, 30.3% were found to contain unclear or ambiguous diagnostic conclusions, including eight cases in which the diagnosis was incorrect. Assessment of molecular annotation revealed that only 18.9% of analyzed lung and colorectal cancer cases included molecular information. Furthermore, among adult\u2010type diffuse gliomas, none of the 55 cases met current World Health Organisation Classification of Tumors of the Central Nervous System 5th Edition (WHO CNS5) diagnostic criteria, with\n                    <jats:italic>IDH<\/jats:italic>\n                    mutation status reported in only 15 cases. Together, these findings highlight substantial ambiguities in ground\u2010truth labeling, incomplete molecular annotation, and limited documentation of dataset provenance and ethical oversight. While HISTAI represents a valuable open\u2010source resource, its effective and responsible use requires careful clinical validation and close collaboration between computational researchers and pathologists.\n                  <\/jats:p>","DOI":"10.1002\/2056-4538.70089","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T03:56:29Z","timestamp":1776311789000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["<scp>HISTAI<\/scp>\n                    : a valuable dataset with a valuable lesson"],"prefix":"10.1002","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6602-0141","authenticated-orcid":false,"given":"Katherine J","family":"Hewitt","sequence":"first","affiliation":[{"name":"Else Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus TUD Dresden University of Technology  Dresden Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0070-3158","authenticated-orcid":false,"given":"Nic G","family":"Reitsam","sequence":"additional","affiliation":[{"name":"Else Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus TUD Dresden University of Technology  Dresden Germany"},{"name":"Pathology, Faculty of Medicine University of Augsburg  Augsburg Germany"},{"name":"Bavarian Center for Cancer Research (BZKF)  Augsburg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4740-6900","authenticated-orcid":false,"given":"Sebastian","family":"Foersch","sequence":"additional","affiliation":[{"name":"Institute of Pathology University Medical Center Mainz  Mainz Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ramona","family":"Erber","sequence":"additional","affiliation":[{"name":"Institut f\u00fcr Pathologie Universit\u00e4t Regensburg  Regensburg Germany"},{"name":"Pathologisches Institut Universit\u00e4tsklinikum Erlangen  Erlangen Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1473-8327","authenticated-orcid":false,"given":"Qinghe","family":"Zeng","sequence":"additional","affiliation":[{"name":"Else Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus TUD Dresden University of Technology  Dresden Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3730-5348","authenticated-orcid":false,"given":"Jakob Nikolas","family":"Kather","sequence":"additional","affiliation":[{"name":"Else Kroener Fresenius Center for Digital Health, Faculty of Medicine and University Hospital Carl Gustav Carus TUD Dresden University of Technology  Dresden Germany"},{"name":"Department of Medicine I, Faculty of Medicine and University Hospital Carl Gustav Carus TUD Dresden University of Technology  Dresden Germany"},{"name":"Medical Oncology, National Center for Tumor Diseases (NCT) University Hospital Heidelberg  Heidelberg Germany"},{"name":"Pathology &amp; Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds  Leeds UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,15]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1038\/ng.2764"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpi.2024.100363"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41597-025-05117-2"},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13000-023-01355-3"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1158\/2767-9764.CRC-24-0243"},{"key":"e_1_2_9_7_1","doi-asserted-by":"crossref","unstructured":"MylesC UmIH MarshallC et al.SurGen: 1020 H&E\u2010stained whole slide images with survival and genetic markers.arXiv2025;https:\/\/doi.org\/10.48550\/arXiv.2502.04946.","DOI":"10.1093\/gigascience\/giaf086"},{"key":"e_1_2_9_8_1","unstructured":"KatherJN HalamaN MarxA.100 000 Histological images of human colorectal cancer and healthy tissue (v0.1) [Data set]. Zenodo2018;https:\/\/doi.org\/10.5281\/zenodo.1214456."},{"key":"e_1_2_9_9_1","unstructured":"NechaevD PchelnikovA IvanovaE.HISTAI: an open\u2010source large\u2010scale whole slide image dataset for computational pathology.arXIV2025;https:\/\/doi.org\/10.48550\/arXiv.2505.12120"},{"key":"e_1_2_9_10_1","unstructured":"NechaevD PchelnikovA IvanovaE.HistAI. Hugging Face. [Accessed 16 March 2026]. Available from:https:\/\/huggingface.co\/histai"},{"key":"e_1_2_9_11_1","volume-title":"Central Nervous System Tumours","author":"WHO Classification of Tumours Editorial Board","year":"2021"},{"key":"e_1_2_9_12_1","unstructured":"NechaevD PchelnikovA IvanovaE.HISTAI\u2010metadata. Hugging Face. [Accessed 16 March 2026]. Available from:https:\/\/huggingface.co\/datasets\/histai\/HISTAI-metadata"},{"key":"e_1_2_9_13_1","unstructured":"HistAI.HistAI: World's Largest Pathology & WSI Dataset and Foundation AI Models. [Accessed 16 March 2026]. Available from:https:\/\/www.hist.ai\/"},{"key":"e_1_2_9_14_1","unstructured":"NorthcuttCG AthalyeA MuellerJ.Pervasive label errors in test sets destabilize machine learning benchmarks.arXiv2021;https:\/\/doi.org\/10.48550\/ARXIV.2103.14749"},{"key":"e_1_2_9_15_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-022-28818-3"},{"key":"e_1_2_9_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.annonc.2020.07.014"},{"key":"e_1_2_9_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ccell.2025.11.002"},{"key":"e_1_2_9_18_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-20603-4"}],"container-title":["The Journal of Pathology: Clinical Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pathsocjournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/2056-4538.70089","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/pathsocjournals.onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/2056-4538.70089","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/pathsocjournals.onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/2056-4538.70089","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,29]],"date-time":"2026-05-29T09:55:27Z","timestamp":1780048527000},"score":1,"resource":{"primary":{"URL":"https:\/\/pathsocjournals.onlinelibrary.wiley.com\/doi\/10.1002\/2056-4538.70089"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,15]]},"references-count":17,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,5]]}},"alternative-id":["10.1002\/2056-4538.70089"],"URL":"https:\/\/doi.org\/10.1002\/2056-4538.70089","archive":["Portico"],"relation":{},"ISSN":["2056-4538","2056-4538"],"issn-type":[{"value":"2056-4538","type":"print"},{"value":"2056-4538","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,15]]},"assertion":[{"value":"2025-10-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-03-20","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-04-15","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70089"}}