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European radiology

ISSN 1432-1084· EN

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29.7 / 100
Journament Score
Poor
Ranked #19,754 of 29,312 scored journals (34,012 indexed)
34 Articles
Scores higher than 32.6% of scored journals
050100
The Journament Score is computed from platform statistics — reader engagement, accessibility, publication timeliness, keyword breadth, community impact and content distribution — into a single 0–100 figure, recalculated as new articles and metadata are indexed. Dimensions that cannot be measured for this journal are excluded rather than estimated. It is independent of the paid AI Quality Analysis, which never affects this score or the ranking. Full methodology →

About This Journal

Short Name Eur Radiol
Abbreviated Name european radiology
ISSN 1432-1084
URL https://www.springer.com/medicine/radiology/journal/330

Quality Profile

7 of 12 dimensions measured
This journal Average of scored journals
Platform statistics — the free Journament Score AI Quality Analysis — separate paid product, ranks nothing

5 of the 12 dimensions could not be measured for this journal. They are left as gaps in the shape rather than plotted as zero.

Show the numbers
Dimension This journal Corpus average
Engagement 30.8 30.4
Accessibility 20.0 20.4
Timeliness 0.0 5.8
Diversity 11.1 24.4
Innovation 70.0 25.7
Community Impact 12.1 5.8
Content Distribution 60.4 88.6
Content Quality — 55.5
Ethics & Transparency — 40.2
Editorial Standards — 33.4
Publication Regularity — 53.2
Geographic Reach — 30.8

Publications Per Year

Articles (34)

2019
Long-term follow-up of persistent pulmonary pure ground-glass nodules with deep learning-assisted nodule segmentation.
Qi, Lin-Lin;Wu, Bo-Tong;Tang, Wei;Zhou, Li-Na;Huang, Yao;Zhao, Shi-Jun;Liu, Li;Li, Meng;Zhang, Li;Feng, Shi-Chao;Hou, Dong-Hui;Zhou, Zhen;Li, Xiu-Li;Wang, Yi-Zhou;Wu, Ning;Wang, Jian-Wei;
450 views DOI Abstract
2019
Encouraging MSK imaging research towards clinical impact is a necessity: opinion paper of the European Society of Musculoskeletal Radiology (ESSR)
Tagliafico, A.
Vol. 29 , pp. 3410-3413
424 views DOI
2020
Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis.
Brugnara, Gianluca;Isensee, Fabian;Neuberger, Ulf;Bonekamp, David;Petersen, Jens;Diem, Ricarda;Wildemann, Brigitte;Heiland, Sabine;Wick, Wolfgang;Bendszus, Martin;Maier-Hein, Klaus;Kickingereder, Philipp;
397 views DOI Abstract
2020
Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?
Bukowski, Mark;Farkas, Robert;Beyan, Oya;Moll, Lorna;Hahn, Horst;Kiessling, Fabian;Schmitz-Rode, Thomas;
391 views DOI Abstract
2020
Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.
Son, Jung Hee;Lee, Seung Soo;Lee, Yedaun;Kang, Bo-Kyeong;Sung, Yu Sub;Jo, SoRa;Yu, Eunsil;
391 views DOI Abstract
2019
Deep learning with ultrasonography: automated classification of liver fibrosis using a deep convolutional neural network.
Lee, Jeong Hyun;Joo, Ijin;Kang, Tae Wook;Paik, Yong Han;Sinn, Dong Hyun;Ha, Sang Yun;Kim, Kyunga;Choi, Choonghwan;Lee, Gunwoo;Yi, Jonghyon;Bang, Won-Chul;
371 views DOI Abstract
2019
CT and MR imaging prior to transcatheter aortic valve implantation: standardisation of scanning protocols, measurements and reporting-a consensus document by the European Society of Cardiovascular Radiology (ESCR).
Francone, Marco;Budde, Ricardo P J;Bremerich, Jens;Dacher, Jean Nicolas;Loewe, Christian;Wolf, Florian;Natale, Luigi;Pontone, Gianluca;Redheuil, Alban;Vliegenthart, Rozemarijn;Nikolaou, Kostantin;Gutberlet, Matthias;Salgado, Rodrigo;
368 views DOI Abstract
2020
Assessment of knee pain from MR imaging using a convolutional Siamese network.
Chang, Gary H;Felson, David T;Qiu, Shangran;Guermazi, Ali;Capellini, Terence D;Kolachalama, Vijaya B;
365 views DOI Abstract
2019
Temporal validation of metabolic nodal response of esophageal cancer to neoadjuvant chemotherapy as an independent predictor of unresectable disease, survival, and recurrence
Findlay, J.
Vol. 29 , pp. 6717-6727
356 views DOI
2019
Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.
Yang, Ruimeng;Wu, Jialiang;Sun, Lei;Lai, Shengsheng;Xu, Yikai;Liu, Xilong;Ma, Ying;Zhen, Xin;
352 views DOI Abstract
2021
Revealing the most common reporting errors through data mining of the report proofreading process
Vosshenrich, J.
Vol. 31 , pp. 2115-2125
133 views DOI
2020
Quantitative assessment of portal hypertension with bi-parametric dual-frequency hepatic MR elastography in mouse models.
Li, Jiahui;Sehrawat, Tejasav S;Chen, Jingbiao;Hilscher, Moira B;Glaser, Kevin J;Arab, Juan P;De Assuncao, Thiago Milech;Simonetto, Douglas A;Mounajjed, Taofic;Manduca, Armando;Ehman, Richard L;Shah, Vijay H;Yin, Meng;
293 views DOI Abstract
2020
Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?
Bukowski, Mark;Farkas, Robert;Beyan, Oya;Moll, Lorna;Hahn, Horst;Kiessling, Fabian;Schmitz-Rode, Thomas;
391 views DOI Abstract
2020
A smaller heart-aorta-angle associates with ascending aortic dilatation and increases wall shear stress.
Kauhanen, S Petteri;Liimatainen, Timo;Kariniemi, Elina;Korhonen, Miika;Parkkonen, Johannes;Vienonen, Juska;Vanninen, Ritva;Hedman, Marja;
290 views DOI Abstract
2020
Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis.
Brugnara, Gianluca;Isensee, Fabian;Neuberger, Ulf;Bonekamp, David;Petersen, Jens;Diem, Ricarda;Wildemann, Brigitte;Heiland, Sabine;Wick, Wolfgang;Bendszus, Martin;Maier-Hein, Klaus;Kickingereder, Philipp;
397 views DOI Abstract
2020
Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.
Son, Jung Hee;Lee, Seung Soo;Lee, Yedaun;Kang, Bo-Kyeong;Sung, Yu Sub;Jo, SoRa;Yu, Eunsil;
391 views DOI Abstract
2020
CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.
Kim, Hyungjin;Lee, Dongheon;Cho, Woo Sang;Lee, Jung Chan;Goo, Jin Mo;Kim, Hee Chan;Park, Chang Min;
348 views DOI Abstract
2020
Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.
Blanc-Durand, Paul;Campedel, Luca;Mule, Sébastien;Jegou, Simon;Luciani, Alain;Pigneur, Frédéric;Itti, Emmanuel;
266 views DOI Abstract
2020
Assessment of knee pain from MR imaging using a convolutional Siamese network.
Chang, Gary H;Felson, David T;Qiu, Shangran;Guermazi, Ali;Capellini, Terence D;Kolachalama, Vijaya B;
365 views DOI Abstract
2020
Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network.
Yasaka, Koichiro;Akai, Hiroyuki;Kunimatsu, Akira;Kiryu, Shigeru;Abe, Osamu;
306 views DOI Abstract
Journament Score
29.7/100 · Poor
Ranked #19,754 of 29,312 scored
(34,012 journals indexed)
Platform Statistics
AI Quality Analysis
Separate paid analysis — does not affect ranking.
Journament

Overall Quality Score

29.7/100

Tier: Poor

The Journament Overall Quality Score is a comprehensive metric that evaluates academic journals across multiple dimensions including engagement, accessibility, diversity, innovation, and community impact.

This score helps researchers, institutions, and publishers understand the holistic quality and impact of a journal beyond traditional metrics.

Engagement Score

30.8/100

Measures user interactions, views, citations, and community involvement with this journal's content.

Higher engagement scores indicate that the journal's content is actively being read, cited, and discussed within the academic community.

Accessibility Score

20.0/100

Evaluates how easily researchers can access journal content, including open access availability, ISSN registration, and indexing.

This metric considers factors such as paywalls, open access policies, and availability across different academic databases and search engines.

Diversity Score

11.1/100

Assesses geographic and institutional diversity of authors, editorial board composition, and topic breadth.

A diverse journal publishes work from various geographic regions, institutions, and covers a broad range of topics within its field.

Innovation Score

70.0/100

Evaluates research novelty, interdisciplinary work, and emerging topics based on AI analysis of article abstracts.

This score reflects how much the journal publishes cutting-edge research, explores new methodologies, and bridges different academic disciplines.

Community Impact Score

12.1/100

Measures scholarly contribution and real-world applications of published research.

This metric evaluates how the journal's research translates into practical applications, policy changes, and benefits to society beyond academia.

Timeliness Score

0.0/100

Evaluates recent publication activity, publication frequency, and currency of research topics.

Higher scores indicate consistent publishing schedules and timely coverage of current research trends.

Content Distribution

60.4/100

Measures how evenly reader attention spreads across the journal's articles, using the Gini coefficient of article clicks.

Higher scores mean readership is distributed across many articles rather than concentrated on one or two.

Ethics & Transparency Score

Not yet measured

Research Integrity (10% weight)

Assesses COPE standards compliance, ethical considerations in research, transparency in methodologies, and reproducibility practices.

This metric ensures the journal maintains high ethical standards and promotes transparent, trustworthy research.

Content Quality Score

Not yet measured

Academic Rigor (20% weight) + Methodology Quality (12%)

Evaluates research methodology soundness, statistical rigor, theoretical framework strength, appropriateness of research methods, data quality, and clarity & readability.

This comprehensive metric ensures published research meets the highest academic standards.

Editorial Diversity Score

Not yet measured

Author Diversity + Interdisciplinary Value (8%)

Measures geographic diversity of authors, institutional variety, editorial board composition, and cross-disciplinary connections.

Diverse editorial teams bring varied perspectives and reduce bias in academic publishing.

Publication Regularity Score

Not yet measured

Assesses consistency of publication schedule, frequency stability, and predictable output patterns.

Regular publication schedules indicate reliable journal operations and consistent workflow management.

Geographic Reach Score

Not yet measured

Evaluates international author representation, global readership distribution, and cross-border research collaboration.

Wide geographic reach indicates global impact and international recognition of the journal's research.