ArticleEuropean journal of nuclear medicine and molecular imaging2019
Artificial intelligence and radiomics in nuclear medicine: potentials and challenges.
Article in European journal of nuclear medicine and molecular imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 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
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- PET-Derived Radiomics and Artificial Intelligence in Breast Cancer: A Systematic Review.International journal of molecular sciences · 2022Pooled it
- Deep learning in nuclear medicine: from imaging to therapy.Annals of nuclear medicine · 2025Review
- Technological Advances in SPECT and SPECT/CT Imaging.Diagnostics (Basel, Switzerland) · 2024Review
- Current Role and Future Prospects of Positron Emission Tomography (PET)/Computed Tomography (CT) in the Management of Breast Cancer.Medicina (Kaunas, Lithuania) · 2024Review
- A machine-learning-based combination of criteria to detect bladder cancer lymph node metastasis on [European radiology · 2023Article
- Radiomics quality score in renal masses: a systematic assessment on current literature.The British journal of radiology · 2022Review
- Artificial intelligence technologies in nuclear medicine.World journal of radiology · 2022Review
- Artificial Intelligence and Precision Medicine: A Perspective.Advances in experimental medicine and biology · 2022Article
- A predictive algorithm using clinical and laboratory parameters may assist in ruling out and in diagnosing MDS.Blood advances · 2021Article
- Applications of artificial intelligence in nuclear medicine image generation.Quantitative imaging in medicine and surgery · 2021Review
- Leveraging Data Science for a Personalized Haemodialysis.Kidney diseases (Basel, Switzerland) · 2020Review
Corrections and comments
- Erratum issued
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence involves a wide range of smart techniques that are applicable to medical services including nuclear medicine. Recent advances in computer power, availability of accumulated digital archives containing large amount of patient images, and records bring new opportunities for the implementation of artificial techniques in nuclear medicine. As a subset of artificial intelligence, machine learning is an emerging tool that possibly perform many clinical tasks. Nuclear medicine community needs to adapt to this fast approaching smart era, to exploit the opportunities and tackle the problems associated with artificial intelligence tools. It is aimed in this editorial to outline the potentials and challenges of artificial intelligence applications in nuclear medicine.
Indexed as
Identifiers
31673788What 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.