ArticleContrast media & molecular imaging2018
Automated Whole-Body Bone Lesion Detection for Multiple Myeloma on
Article in Contrast media & molecular imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.
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
34 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Deep learning applications in visual data for benign and malignant hematologic conditions: a systematic review and visual glossary.Haematologica · 2023Pooled it
- Artificial intelligence applied to musculoskeletal oncology: a systematic review.Skeletal radiology · 2022Pooled it
- A Meta-Analysis of Deep-Learning-Based Fusion of Positron Emission Tomography and Computed Tomography in Oncologic Imaging.Journal of imaging informatics in medicine · 2026Review
- Multi-modal co-learning with attention mechanism for head and neck tumor segmentation onEJNMMI physics · 2024Article
- Enhancing diagnostic accuracy of multiple myeloma through ML-driven analysis of hematological slides: new dataset and identification model to support hematologists.Scientific reports · 2024Article
- Curation of myeloma observational study MALIMAR using XNAT: solving the challenges posed by real-world data.Insights into imaging · 2024Article
- Artificial intelligence-driven radiomics: developing valuable radiomics signatures with the use of artificial intelligence.BJR artificial intelligence · 2024Article
- Recent advances in imaging and artificial intelligence (AI) for quantitative assessment of multiple myeloma.American journal of nuclear medicine and molecular imaging · 2024Review
- Positron Emission Tomography-Derived Radiomics and Artificial Intelligence in Multiple Myeloma: State-of-the-Art.Journal of clinical medicine · 2023Review
- Cluster analysis of autoencoder-extracted FDG PET/CT features identifies multiple myeloma patients with poor prognosis.Scientific reports · 2023Article
- Deep learning image segmentation approaches for malignant bone lesions: a systematic review and meta-analysis.Frontiers in radiology · 2023Review
- Artificial intelligence and its applications in digital hematopathology.Blood science (Baltimore, Md.) · 2022Article
- Deep learning-based detection of parathyroid adenoma byAnnals of nuclear medicine · 2022Article
- Machine Learning and Deep Learning Applications in Multiple Myeloma Diagnosis, Prognosis, and Treatment Selection.Cancers · 2022Review
- APU-Net: An Attention Mechanism Parallel U-Net for Lung Tumor Segmentation.BioMed research international · 2022Article
- Segmentation and Classification of White Blood Cells Using the UNet.Contrast media & molecular imaging · 2022Article
- Article
- Artificial intelligence in molecular imaging.Annals of translational medicine · 2021Review
- A review of the application of machine learning in molecular imaging.Annals of translational medicine · 2021Review
- Machine Learning Applications in the Diagnosis of Benign and Malignant Hematological Diseases.Clinical hematology international · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The identification of bone lesions is crucial in the diagnostic assessment of multiple myeloma (MM).
Indexed as
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.