ReviewPET clinics2021
Potential Applications of Artificial Intelligence and Machine Learning in Radiochemistry and Radiochemical Engineering.
Review in PET clinics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026Review
- Review
- Investigation on the isotopic exchange radiofluorination of the pentafluorosulfanyl group.Organic & biomolecular chemistry · 2025Article
- Optimizing Cancer Treatment: Exploring the Role of AI in Radioimmunotherapy.Diagnostics (Basel, Switzerland) · 2025Review
- Copper-mediated radiochemistry: historical impact, current trends, and future possibilities.Npj imaging · 2025Review
- Radiochemistry: A Hot Field with Opportunities for Cool Chemistry.ACS central science · 2023Review
- Proceedings of international symposium of trends in radiopharmaceuticals 2023 (ISTR-2023).EJNMMI radiopharmacy and chemistry · 2023Review
- The Development and Validation of Radiopharmaceuticals Targeting Bacterial Infection.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023Article
- Accelerating radiochemistry development: Automated robotic platform for performing up to 64 droplet radiochemical reactions in a morning.Chemical engineering journal (Lausanne, Switzerland : 1996) · 2023Article
- Artificial Intelligence in Nuclear Medicine: Opportunities, Challenges, and Responsibilities Toward a Trustworthy Ecosystem.Journal of nuclear medicine : official publication, Society of Nuclear Medicine · 2023Article
- Review
- Copper-Mediated Radiocyanation of Unprotected Amino Acids and Peptides.Journal of the American Chemical Society · 2022Article
- SThe Journal of organic chemistry · 2021Article
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
Artificial intelligence and machine learning are poised to disrupt PET imaging from bench to clinic. In this perspective, the authors offer insights into how the technology could be applied to improve the radiosynthesis of new radiopharmaceuticals for PET imaging, including identification of an optimal labeling approach as well as strategies for radiolabeling reaction optimization.
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.