ReviewThe British journal of radiology2020
Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century.
Review in The British journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 4 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
39 citing papers in PubMed, 4 syntheses or guidelines pooled it, 95 citations in OpenAlex.
- Detection of cerebral aneurysms using artificial intelligence: a systematic review and meta-analysis.Journal of neurointerventional surgery · 2023Pooled it
- Joint EANM/SNMMI guideline on radiomics in nuclear medicine : Jointly supported by the EANM Physics Committee and the SNMMI Physics, Instrumentation and Data Sciences Council.European journal of nuclear medicine and molecular imaging · 2023Guideline
- Ethics of AI in Radiology: A Review of Ethical and Societal Implications.Frontiers in big data · 2022Pooled it
- Promises of artificial intelligence in neuroradiology: a systematic technographic review.Neuroradiology · 2020Pooled it
- Assessing the Evolution and Influence of Medical Open Databases on Biomedical Research and Health Care Innovation: A 25-Year Perspective With a Focus on Privacy and Privacy-Enhancing Technologies.Journal of medical Internet research · 2026Article
- Artificial intelligence for optimization of immunotherapy: current applications and transformative potential.Frontiers in immunology · 2026Review
- Recent applications of artificial intelligence in cancer radiotherapy and immunotherapy: current status and future directions.Frontiers in immunology · 2026Review
- Artificial intelligence in radiology: promising tool or overhyped trend?Annals of medicine and surgery (2012) · 2025Article
- Artificial Intelligence for Multiscale Spatial Analysis in Oncology: Current Applications and Future Implications.International journal of molecular sciences · 2025Review
- The dark matter in cancer immunology: beyond the visible- unveiling multiomics pathways to breakthrough therapies.Journal of translational medicine · 2025Review
- AI-Driven Advances in Low-Dose Imaging and Enhancement-A Review.Diagnostics (Basel, Switzerland) · 2025Review
- DWI-based Biologically Interpretable Radiomic Nomogram for Predicting 1-year Biochemical Recurrence after Radical Prostatectomy: A Deep Learning, Multicenter Study.Current medical imaging · 2025Article
- Comparison of radiological interpretation made by veterinary radiologists and state-of-the-art commercial AI software for canine and feline radiographic studies.Frontiers in veterinary science · 2025Article
- AI and machine learning in medical imaging: key points from development to translation.BJR artificial intelligence · 2024Review
- Clinical applications of artificial intelligence in radiology.The British journal of radiology · 2023Review
- Translation of AI into oncology clinical practice.Oncogene · 2023Review
- Predicting intensive care need for COVID-19 patients using deep learning on chest radiography.Journal of medical imaging (Bellingham, Wash.) · 2023Article
- The influence of artificial intelligence on the work of the medical physicist in radiotherapy practice: a short review.BJR open · 2023Review
- Explainability and controllability of patient-specific deep learning with attention-based augmentation for markerless image-guided radiotherapy.Medical physics · 2023Article
- Beyond high hopes: A scoping review of the 2019-2021 scientific discourse on machine learning in medical imaging.PLOS digital health · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
Abstract
Advances in computing hardware and software platforms have led to the recent resurgence in artificial intelligence (AI) touching almost every aspect of our daily lives by its capability for automating complex tasks or providing superior predictive analytics. AI applications are currently spanning many diverse fields from economics to entertainment, to manufacturing, as well as medicine. Since modern AI's inception decades ago, practitioners in radiological sciences have been pioneering its development and implementation in medicine, particularly in areas related to diagnostic imaging and therapy. In this anniversary article, we embark on a journey to reflect on the learned lessons from past AI's chequered history. We further summarize the current status of AI in radiological sciences, highlighting, with examples, its impressive achievements and effect on re-shaping the practice of medical imaging and radiotherapy in the areas of computer-aided detection, diagnosis, prognosis, and decision support. Moving beyond the commercial hype of AI into reality, we discuss the current challenges to overcome, for AI to achieve its promised hope of providing better precision healthcare for each patient while reducing cost burden on their families and the society at large.
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.