ArticleRadiology. Artificial intelligence2020
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Article in Radiology. Artificial intelligence, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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41citing papers in PubMed
–field-weighted citation impact
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
41 citing papers in PubMed.
- DWI-derived intratumoral, peritumoral, and habitat features for preoperative prediction of lymph node metastasis in early-stage cervical cancer using machine learning method.Abdominal radiology (New York) · 2026Article
- Integration of Node-RADS and Habitat Radiomics for Predicting Occult Nodal Metastasis in Bladder Cancer.Annals of surgical oncology · 2026Article
- Article
- Heterogeneity Analyzed by CT-Based Habitat Analysis for Clinical Management of Cancers: A Narrative Review.The Kaohsiung journal of medical sciences · 2026Review
- Clinical utility and future directions of FDG-PET in rectal cancer management.Annals of nuclear medicine · 2026Review
- Radiomics and artificial intelligence in precision radiotherapy for cervical cancer: a narrative review.Frontiers in oncology · 2026Review
- Radiomics based on habitat analysis in predicting parametrial invasion of early stage cervical cancer.Frontiers in oncology · 2026Article
- An exploratory assessment of early and delta PET radiomic features for outcome prediction in locally advanced cervical cancer.European journal of nuclear medicine and molecular imaging · 2025Article
- MRI-based Intra- and Peritumoral Heterogeneity in Hepatocellular Carcinoma for Microvascular Invasion Prediction and Prognostic Risk Stratification.Radiology. Imaging cancer · 2025Article
- Habitat-based transformer model in pretreatmentBMC cancer · 2025Article
- Pre-Treatment PET Radiomics for Prediction of Disease-Free Survival in Cervical Cancer.Cancers · 2025Article
- Application of artificial intelligence in assisting treatment of gynecologic tumors: a systematic review.Visual computing for industry, biomedicine, and art · 2025Review
- miR-21-5p inhibitor enhances the radiosensitivity of human cervical cancer cells via blocking CPEB3-mediated CDK1/cyclin B pathway.Biochemistry and biophysics reports · 2025Article
- Advancements in Acute Pulmonary Embolism Diagnosis and Treatment: A Narrative Review of Emerging Imaging Techniques and Intravascular Interventions.Journal of cardiovascular development and disease · 2025Review
- The value of habitat analysis based onBMC medical imaging · 2025Article
- Habitat radiomics assists radiologists in accurately diagnosing lymph node metastasis of adenocarcinoma of the esophagogastric junction.Insights into imaging · 2025Article
- Habitat radiomics analysis for progression free survival and immune-related adverse reaction prediction in non-small cell lung cancer treated by immunotherapy.Journal of translational medicine · 2025Article
- Habitat Analysis in Tumor Imaging: Advancing Precision Medicine Through Radiomic Subregion Segmentation.Cancer management and research · 2025Review
- Incremental diagnostic value of tumor habitat radiomics for risk stratification in thymic epithelial tumors.Frontiers in oncology · 2025Article
- The promise and limitations of artificial intelligence in CTPA-based pulmonary embolism detection.Frontiers in medicine · 2025Review
Corrections and comments
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Authors and funding
9 authors.
Wei MuDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).ORCID 0000-0001-7970-8666
Ying LiangDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).
Lawrence O HallDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).ORCID 0000-0002-7898-8456
Yan TanDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).
Yoganand BalagurunathanDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).ORCID 0000-0002-5598-4727
Robert WenhamDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).
Ning WuDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).ORCID 0000-0001-6971-2995
Jie TianDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).
Robert J GilliesDepartment of Cancer Physiology (W.M., Y.T., Y.B., R.J.G.) and Gynecologic Oncology (R.W.), H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Dr, Tampa, FL 33612; Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China (Y.L., N.W.); Department of Computer Science and Engineering, University of South Florida, Tampa, Fla (L.O.H.); Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Medicine, Beihang University, Beijing, China (J.T.); and CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.).
Funding
Radiomics of NSCLCU01CA143062 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI GILLIES, ROBERT J., SCHABATH, MATTHEW B. · 2010 to 2020
$5.7M(PQC4) Habitats in Prostate CancerR01CA190105 · NCI · H. LEE MOFFITT CANCER CTR & RES INST · PI BALAGURUNATHAN, YOGANAND, GILLIES, ROBERT J. · 2014 to 2017
$2.8MNCI NIH HHS R01 CA190105NCI NIH HHS U01 CA143062
Abstract
purposeTo determine if quantitative features extracted from pretherapy fluorine 18 fluorodeoxyglucose ( MATERIALS AND
methodsIn this retrospective study, PET/CT images and outcomes were curated from 154 patients with locally advanced cervical cancer, who underwent chemoradiotherapy from two institutions between March 2008 and June 2016, separated into independent training (
resultsThe radiomics nomograms constructed with T stage, lymph node status, and radiomics signatures resulted in significantly better performance for the estimation of PFS (Harrell concordance index [C-index], 0.85 for training and 0.82 for test) and OS (C-index, 0.86 for training and 0.82 for test) compared with International Federation of Gynecology and Obstetrics staging system (C-index for PFS, 0.70 for training [
conclusionPrognostic models were generated and validated from quantitative analysis of
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.