| no |
title |
author |
magazine |
year |
volume |
issue |
page(s) |
type |
| 1 |
Adenosine triphosphate (ATP): a safe and effective vasodilator for stress perfusion cardiac magnetic resonance imaging
|
Kong, H.
|
|
|
78 |
2 |
p. e71-e76
|
article
|
| 2 |
AI and ML in radiology: Making progress
|
Rockall, A.G.
|
|
|
78 |
2 |
p. 81-82
|
article
|
| 3 |
Assessment of the degree of arterial stenosis in intracranial atherosclerosis using 3D high-resolution MRI: comparison with time-of-flight MRA, contrast-enhanced MRA, and DSA
|
Zhao, D.-L.
|
|
|
78 |
2 |
p. e63-e70
|
article
|
| 4 |
Clinical analysis of prophylactic para-aortic intensity-modulated radiation in cervical cancer
|
Jin, G.
|
|
|
78 |
2 |
p. e77-e84
|
article
|
| 5 |
Comparison of single- and dual-energy CT combined with artificial intelligence for the diagnosis of pulmonary nodules
|
X. Zhu,
|
|
|
78 |
2 |
p. e99-e105
|
article
|
| 6 |
Contents
|
|
|
|
78 |
2 |
p. iii-v
|
article
|
| 7 |
Cost drivers in endovascular pulmonary embolism interventions
|
Callese, T.E.
|
|
|
78 |
2 |
p. e143-e149
|
article
|
| 8 |
DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology
|
Vasey, B.
|
|
|
78 |
2 |
p. 130-136
|
article
|
| 9 |
Glioma radiogenomics and artificial intelligence: road to precision cancer medicine
|
Mahajan, A.
|
|
|
78 |
2 |
p. 137-149
|
article
|
| 10 |
Glomus tumours of the knee: a case series
|
Stacy, G.S.
|
|
|
78 |
2 |
p. e123-e130
|
article
|
| 11 |
Identification of ovarian endometriotic cysts in cystic lesions of the ovary by amide proton transfer-weighted imaging and R2∗ mapping
|
Li, Y.
|
|
|
78 |
2 |
p. e106-e112
|
article
|
| 12 |
Introduction to radiomics for a clinical audience
|
McCague, C.
|
|
|
78 |
2 |
p. 83-98
|
article
|
| 13 |
Machine-learning algorithm in acute stroke: real-world experience
|
Chan, N.
|
|
|
78 |
2 |
p. e45-e51
|
article
|
| 14 |
Potential ultrasonic anatomical markers of obstructive sleep apnoea–hypopnoea syndrome
|
Lun, H.-M.
|
|
|
78 |
2 |
p. e137-e142
|
article
|
| 15 |
Predictive value of peritumour radiomics in the diagnosis of benign and malignant pulmonary nodules with halo sign
|
Tan, M.
|
|
|
78 |
2 |
p. e52-e62
|
article
|
| 16 |
Radiomics nomogram in aiding preoperatively dilatation and curettage in differentiating type II and type I endometrial cancer
|
Liu, X.-F.
|
|
|
78 |
2 |
p. e29-e36
|
article
|
| 17 |
Radiomics signature based on CECT for non-invasive prediction of response to anti-PD-1 therapy in patients with hepatocellular carcinoma
|
Cui, H.
|
|
|
78 |
2 |
p. e37-e44
|
article
|
| 18 |
RCR meetings
|
|
|
|
78 |
2 |
p. I
|
article
|
| 19 |
Re: A bump in the night: a 15-year retrospective analysis of urgent inpatient and emergency CT reporting out of hours in a tertiary referral centre
|
Jackson, M.R.
|
|
|
78 |
2 |
p. e153
|
article
|
| 20 |
Re: detection rate of MR myelography without intrathecal gadolinium in patients with newly diagnosed spontaneous intracranial hypotension
|
Carlton Jones, L.
|
|
|
78 |
2 |
p. e150-e151
|
article
|
| 21 |
Re: gender representation within radiology conferences in the UK in 2021
|
Mills, S.J.
|
|
|
78 |
2 |
p. e152
|
article
|
| 22 |
Retrospective study of the incidence of sarcoidosis-like reaction in patients treated with immunotherapy
|
Li, Y.
|
|
|
78 |
2 |
p. e131-e136
|
article
|
| 23 |
Splenic embolisation practices within the UK: a national survey
|
Jenkins, P.
|
|
|
78 |
2 |
p. e85-e88
|
article
|
| 24 |
The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States
|
Milam, M.E.
|
|
|
78 |
2 |
p. 115-122
|
article
|
| 25 |
The frequency of change in five-point scale score with a Bayesian penalised likelihood PET reconstruction algorithm on interim FDG PET-CT and its potential implications for therapy decisions in Hodgkin's lymphoma
|
Subesinghe, M.
|
|
|
78 |
2 |
p. e89-e98
|
article
|
| 26 |
The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications
|
Silkens, M.E.W.M.
|
|
|
78 |
2 |
p. 107-114
|
article
|
| 27 |
The top 100 most cited articles on artificial intelligence in radiology: a bibliometric analysis
|
Hughes, H.
|
|
|
78 |
2 |
p. 99-106
|
article
|
| 28 |
Transarterial chemoembolisation for very early and early stage hepatocellular carcinoma: single-centre experience
|
Hashem, E.
|
|
|
78 |
2 |
p. e113-e122
|
article
|
| 29 |
Trends in clinical validation and usage of US Food and Drug Administration-cleared artificial intelligence algorithms for medical imaging
|
Khunte, M.
|
|
|
78 |
2 |
p. 123-129
|
article
|
| 30 |
Utilisation of deep learning for COVID-19 diagnosis
|
Aslani, S.
|
|
|
78 |
2 |
p. 150-157
|
article
|
Journal description