ArticleBMC medicine2021
Accurate diagnosis of colorectal cancer based on histopathology images using artificial intelligence.
Open access · goldAbstract readMulticenter Study
In one paragraph
Article in BMC medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 2 of them syntheses that pooled it.
0numbers the graph read from it
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79citing papers in PubMed, 2 pooled it
16.7field-weighted citation impact, top 1% of its field
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Who cites it
79 citing papers in PubMed, 2 syntheses or guidelines pooled it, 167 citations in OpenAlex.
- Advancements in Image-Based Analyses for Morphology and Staging of Colon Cancer: A Comprehensive Review.BioMed research international · 2025Pooled it
- The Impact of Artificial Intelligence in Improving Polyp and Adenoma Detection Rate During Colonoscopy: Systematic-Review and Meta-Analysis.Asian Pacific journal of cancer prevention : APJCP · 2023Pooled it
- COOT-CNN: joint architecture and training-strategy optimization for binary colorectal histology patch classification.Scientific reports · 2026Article
- A novel model for assessing lymph node metastasis and the immune microenvironment in breast cancer by integrating digital pathology images and transcriptomics.Discover oncology · 2026Article
- Evolving Landscape for Artificial Intelligence in the Diagnosis and Histopathologic Assessment of Oral and Oropharyngeal Cancer.Head and neck pathology · 2026Review
- Uncovering Hidden Prognostic Patterns in Colorectal Cancer Histology Using Unsupervised Learning: A Computational Pathology Study.Bioengineering (Basel, Switzerland) · 2026Article
- Causal Inference and Prognostic Modeling in Colorectal Cancer through Integration of Computational Pathology and Mendelian Randomization.Annals of surgical oncology · 2026Article
- Integrating histopathology and immune marker analysis for machine learning-based colorectal cancer prognostics.Diagnostic pathology · 2026Article
- The consensus molecular subtypes of esophageal squamous cell carcinoma.Signal transduction and targeted therapy · 2026Article
- Multimodal deep learning for survival prediction and biomarker discovery in non-small cell lung cancer.BioData mining · 2026Article
- Next-Generation Sequencing-Based Detection ofGenes · 2026Article
- Deep learning-based multimodal fusion of MRI and whole slide image for predicting neoadjuvant therapy response in locally advanced head and neck squamous cell carcinoma.BMC medical imaging · 2026Article
- Diagnostic accuracy of deep learning models for colorectal cancer detection in histopathological whole-slide images: a systematic review and diagnostic test accuracy meta-analysis.Frontiers in oncology · 2026Review
- Advancements in artificial intelligence for cancer diagnosis and prognosis prediction: current applications and emerging opportunities.Frontiers in cell and developmental biology · 2026Review
- IDF-Net: Interpretable Dynamic Fusion Network for Colorectal Cancer Diagnosis Using Cross-Modal Imaging.Diagnostics (Basel, Switzerland) · 2025Article
- Integrating artificial intelligence in healthcare: applications, challenges, and future directions.Future science OA · 2025Review
- Early-stage lung adenocarcinoma affects DNA methylation and gene expression in adjacent tissues.EMBO reports · 2025Article
- Efficient deep neural networks for cancer detection on histopathology combining attention and image downsampling.Scientific reports · 2025Article
- Photoacoustic-Integrated Multimodal Approach for Colorectal Cancer Diagnosis.ACS biomaterials science & engineering · 2025Review
- ColoViT: a synergistic integration of EfficientNet and vision transformers for advanced colon cancer detection.Journal of cancer research and clinical oncology · 2025Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
54 authors at 19 institutions in 2 countries.
K S Wang *Department of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
G Yu *Department of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
C Xu *Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, 73104, USA.
X H Meng *Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, 410081, Hunan, China.
J ZhouDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
C ZhengDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
Z DengDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
L ShangDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
R LiuDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
S SuDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
X ZhouDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
Q LiDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
J LiDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
J WangDepartment of Pathology, Xiangya Hospital, Central South University, Changsha, 410078, Hunan, China.
K MaDepartment of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
J QiDepartment of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
Z HuDepartment of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
P TangDepartment of Pathology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
J DengDepartment of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA.
X QiuCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
B Y LiCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
W D ShenCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
R P QuanCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
J T YangCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
L Y HuangCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
Y XiaoCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China.
Z C YangDepartment of Pharmacology, Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, 410078, Hunan, China.
Z LiSchool of Life Sciences, Central South University, Changsha, 410013, Hunan, China.
S C WangCollege of Information Science and Engineering, Hunan Normal University, Changsha, 410081, Hunan, China.
H RenDepartment of Pathology, Gongli Hospital, Second Military Medical University, Shanghai, 200135, China.
C LiangPathological Laboratory of Adicon Medical Laboratory Co., Ltd, Hangzhou, 310023, Zhejiang, China.
W GuoDepartment of Pathology, First Affiliated Hospital of Hunan Normal University, The People's Hospital of Hunan Province, Changsha, 410005, Hunan, China.
Y LiDepartment of Pathology, First Affiliated Hospital of Hunan Normal University, The People's Hospital of Hunan Province, Changsha, 410005, Hunan, China.
H XiaoDepartment of Pathology, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
Y GuDepartment of Pathology, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
J P YunDepartment of Pathology, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
D HuangDepartment of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, China.
Z SongDepartment of Pathology, Chinese PLA General Hospital, Beijing, 100853, China.
X FanDepartment of Pathology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, 210008, China.
L ChenDepartment of Pathology, The first affiliated hospital, Air Force Medical University, Xi'an, 710032, China.
X YanInstitute of Pathology and southwest cancer center, Southwest Hospital, Third Military Medical University, Chongqing, 400038, China.
Z LiDepartment of Pathology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China.
Z C HuangDepartment of Biomedical Engineering, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
J HuangDepartment of Anatomy and Neurobiology, School of Basic Medical Science, Central South University, Changsha, 410013, Hunan, China.
J LuttrellSchool of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA.
C Y ZhangSchool of Computing Sciences and Computer Engineering, University of Southern Mississippi, Hattiesburg, MS, 39406, USA.
W ZhouCollege of Computing, Michigan Technological University, Houghton, MI, 49931, USA.
K ZhangDepartment of Computer Science, Bioinformatics Facility of Xavier NIH RCMI Cancer Research Center, Xavier University of Louisiana, New Orleans, LA, 70125, USA.
C YiDepartment of Pathology, Ochsner Medical Center, New Orleans, LA, 70121, USA.
C WuDepartment of Statistics, Florida State University, Tallahassee, FL, 32306, USA.
H ShenDepartment of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA.
Y P WangDepartment of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA.
H M XiaoCenters of System Biology, Data Information and Reproductive Health, School of Basic Medical Science, School of Basic Medical Science, Central South University, Changsha, 410008, Hunan, China. hmxiao@csu.edu.cn.
H W DengDepartment of Deming Department of Medicine, Tulane Center of Biomedical Informatics and Genomics, Tulane University School of Medicine, 1440 Canal Street, Suite 1610, New Orleans, LA, 70112, USA. hdeng2@tulane.edu.
Central South University · CNXiangya Hospital Central South University · CNHunan Normal University · CNTulane University · USThird Xiangya Hospital · CNUniversity of Southern Mississippi · USAir Force Medical University · CNArmy Medical University · CNChinese PLA General Hospital · CNFlorida State University · USFudan University Shanghai Cancer Center · CNGuangdong Academy of Medical Sciences · CNMichigan Technological University · USNanjing Drum Tower Hospital · CNOchsner Medical Center · USSecond Military Medical University · CNSun Yat-sen University Cancer Center · CNUniversity of Oklahoma Health Sciences Center · USXavier University of Louisiana · US
Funding
Xavier RCMI Renewal Application-Research Infrastructure CoreU54MD007595 · NIMHD · XAVIER UNIVERSITY OF LOUISIANA · PI LaKeisha Williams · 2019 to 2026
$41.9MTulane COBRE in Cardiometabolic Diseases Clinical Research CoreP20GM109036 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI Yoriko Heianza · 2016 to 2026
$25.3MTrans-omics Integration of Multi-omics Studies for OsteoporosisU19AG055373 · NIA · TULANE UNIVERSITY OF LOUISIANA · PI Qi Zhao · 2017 to 2026
$24.3MXavier's RCMI Cancer Research ProgramG12MD007595 · NIMHD · XAVIER UNIVERSITY OF LOUISIANA · PI D'AMOUR, GENE, WANG, GUANGDI · 2012 to 2018
$15.7MNutrigenetics and Nutrigenomics for Precision Weight-Loss Diet InterventionsR01DK115679 · NIDDK · TULANE UNIVERSITY OF LOUISIANA · PI Lu Qi · 2018 to 2026
$5.3MEpigenomewide DNA Methylation Study for Osteoporosis RiskR01AR059781 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2012 to 2016
$3.1MDecoding Methylation Mediated Epigenomic Contributions to Male OsteoporosisR01AR069055 · NIAMS · TULANE UNIVERSITY OF LOUISIANA · PI DENG, HONG-WEN · 2017 to 2021
$2.9MIntegration of brain imaging with genomic and epigenomic dataR01MH104680 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI CALHOUN, VINCE D, DENG, HONG-WEN · 2014 to 2017
$2.1MIntegration of fMRI imaging, genomics, network and biological knowledgeR01MH107354 · NIMH · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2015 to 2018
$1.9MIntegration of multiscale genomic data for comprehensive analysis of complex diseR01GM109068 · NIGMS · TULANE UNIVERSITY OF LOUISIANA · PI WANG, YU-PING · 2014 to 2018
$1.6MNIAMS NIH HHS R01 AR059781NIAMS NIH HHS R01 AR069055NIA NIH HHS U19 AG055373NIDDK NIH HHS R01 DK115679NIGMS NIH HHS P20 GM109036NIGMS NIH HHS R01 GM109068NIMHD NIH HHS U54 MD007595NIMH NIH HHS R01 MH104680NIMH NIH HHS R01 MH107354
Abstract
backgroundAccurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients' treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses.
methodsBased on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany.
resultsOur innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells.
conclusionsThis first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.
Indexed as
Colorectal NeoplasmsDeep LearningArtificial IntelligenceHumansNeural Networks, ComputerROC CurveCancer diagnosisColorectal cancerDeep learningHistopathology image
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