ReviewEuropean journal of hybrid imaging2020
Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy.
Review in European journal of hybrid imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed.
- Deep learning-based metal artifact reduction in CT for head and neck radiotherapy.Physics and imaging in radiation oncology · 2026Review
- Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026Review
- The complementary roles of oversight, education, and collaboration in the responsible integration of artificial intelligence in radiation medicine: White paper of CADRA.Journal of applied clinical medical physics · 2026Review
- AI-Powered MRI Radiomics and Deep Learning for Preoperative Prediction of Cavernous Sinus Invasion in Pituitary Adenomas: A Clinically Oriented Review of Current Evidence.Neuroimage. Reports · 2026Review
- Distinguishing cancer patients' mild and severe symptoms in radiotherapy via zero-shot and few-shot large language model-based probabilistic prompts.BioData mining · 2026Article
- ¹⁸F-FDG PET radiomics and machine learning for virtual biopsy and treatment decisions in lymphoma: a multicenter study.Physical and engineering sciences in medicine · 2026Article
- Sparse-view reconstruction and noise reduction in 99m Tc-prostate specific membrane antigen prostate imaging.Nuclear medicine communications · 2026Article
- Enhanced Pelvic CT Segmentation via Deep Learning: A Study on Loss Function Effects.Journal of imaging informatics in medicine · 2026Article
- Supervised Volumetric Segmentation of White and Gray Matter from Brain Positron Emission Tomography Images Using Magnetic Resonance Labels.Journal of medical signals and sensors · 2026Article
- Automatic Lugano staging for risk stratification in lymphoma: a multicenter PET radiomics and machine learning study with survival analysis.Nuclear medicine communications · 2025Article
- Integrative Machine Learning Model for Overall Survival Prediction in Breast Cancer Using Clinical and Transcriptomic Data.Biology · 2025Article
- Automated pulmonary nodule classification from low-dose CT images using ERBNet: an ensemble learning approach.Medical & biological engineering & computing · 2025Article
- A feasibility study of deep learning prediction model for VMAT patient-specific QA.Frontiers in oncology · 2025Article
- Advancements in Artificial Intelligence in Noninvasive Cardiac Imaging: A Comprehensive Review.Clinical cardiology · 2025Review
- Review
- Deep learning-based partial volume correction in standard and low-dose positron emission tomography-computed tomography imaging.Quantitative imaging in medicine and surgery · 2024Article
- Verification of image quality improvement of low-count bone scintigraphy using deep learning.Radiological physics and technology · 2024Article
- Automated segmentation of lesions and organs at risk on [Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Article
- Radiomics and Artificial Intelligence in Radiotheranostics: A Review of Applications for Radioligands Targeting Somatostatin Receptors and Prostate-Specific Membrane Antigens.Diagnostics (Basel, Switzerland) · 2024Review
- Joint Brain Tumor Segmentation from Multi-magnetic Resonance Sequences through a Deep Convolutional Neural Network.Journal of medical signals and sensors · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
This brief review summarizes the major applications of artificial intelligence (AI), in particular deep learning approaches, in molecular imaging and radiation therapy research. To this end, the applications of artificial intelligence in five generic fields of molecular imaging and radiation therapy, including PET instrumentation design, PET image reconstruction quantification and segmentation, image denoising (low-dose imaging), radiation dosimetry and computer-aided diagnosis, and outcome prediction are discussed. This review sets out to cover briefly the fundamental concepts of AI and deep learning followed by a presentation of seminal achievements and the challenges facing their adoption in clinical setting.
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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.