ArticleTranslational oncology2014
NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures.
Article in Translational oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
45 citing papers in PubMed.
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- Conventional and advanced imaging throughout the cycle of care of gliomas.Neurosurgical review · 2021Review
- State of machine and deep learning in histopathological applications in digestive diseases.World journal of gastroenterology · 2021Review
- Targeting Treatment Resistance in Head and Neck Squamous Cell Carcinoma - Proof of Concept for CT Radiomics-Based Identification of Resistant Sub-Volumes.Frontiers in oncology · 2021Article
- 3D DenseNet Deep Learning Based Preoperative Computed Tomography for Detecting Myasthenia Gravis in Patients With Thymoma.Frontiers in oncology · 2021Article
- Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges.Neuro-oncology advances · 2020Article
- Clinicoradiopathological features and prognosis according to genomic alterations in patients with resected lung adenocarcinoma.Journal of thoracic disease · 2020Article
- Radiomics: an overview in lung cancer management-a narrative review.Annals of translational medicine · 2020Review
- Detection of response to tumor microenvironment-targeted cellular immunotherapy using nano-radiomics.Science advances · 2020Article
- Dataset of segmented nuclei in hematoxylin and eosin stained histopathology images of ten cancer types.Scientific data · 2020Article
- PRISM: A Platform for Imaging in Precision Medicine.JCO clinical cancer informatics · 2020Article
- Open access image repositories: high-quality data to enable machine learning research.Clinical radiology · 2020Article
- Radiogenomics of breast cancer using dynamic contrast enhanced MRI and gene expression profiling.Cancer imaging : the official publication of the International Cancer Imaging Society · 2019Article
- Robust Histopathology Image Analysis: to Label or to Synthesize?Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 2019Article
- Radiomic features from computed tomography to differentiate invasive pulmonary adenocarcinomas from non-invasive pulmonary adenocarcinomas appearing as part-solid ground-glass nodules.Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2019Article
- Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma.Cancer medicine · 2018Article
- Comprehensive Computed Tomography Radiomics Analysis of Lung Adenocarcinoma for Prognostication.The oncologist · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.
Identifiers
What OpenQuestion holds
Registered trials
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.