LIDC-IDRI

data category: Medical and clinical datasets · 0 papers in the last 7 days

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Clinical records, medical images and physiological signals used in medical machine learning.

Names searched for: LIDC-IDRI

Key findings#

From Nov 2023 to Oct 2026, 32 archived papers mentioned LIDC-IDRI in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Feb 2025 (6).
No paper of the tracked journals mentioned LIDC-IDRI in the last 30 days (2026-10-07 to 2026-11-05).
From 2017 to 2026 (so far), LIDC-IDRI was mentioned in 65 papers in the tracked journals, most of them in AI (65).
11 of them were published in 2025, against 2 in 2017.
Since 2023, the institutions with the most of these papers were Northwestern Polytechnical University (2), University of Sharjah (2) and Aarhus University (1).
The journals publishing most of them were Neural Computing and Applications (7), Expert Systems with Applications (6) and Artificial Intelligence Review (5).
The most-cited of them is “Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT” (Information Fusion, 2017), with 286 citations.
Papers use LIDC-IDRI most often with ImageNet (12), Kaggle (7) and BraTS (6); it has 9 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

Mentions over 36 months#

Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)
Trend	Nov 23–Oct 24	Nov 24–Oct 25	Nov 25–Oct 26	36 months
	11	13	8	32

Papers per year#

20172026 (so far)

Papers per publication year and category
Category	2017	2018	2019	2020	2021	2022	2023	2024	2025	2026 (so far)
AI	2	4	6	5	4	8	5	12	11	8
All categories	2	4	6	5	4	8	5	12	11	8

Where the papers come from#

Journals with the most papers, since 2023
#	Journal	Papers
1	Neural Computing and Applications	7
2	Expert Systems with Applications	6
3	Artificial Intelligence Review	5
4	Information Fusion	3
5	Pattern Recognition	2
6	Applied Intelligence	2
7	Knowledge-Based Systems	2
8	Cognitive Computation	2
9	Information Sciences	1
10	Machine Learning	1

Institutions with the most papers, since 2023
#	Institution	Papers
1	Northwestern Polytechnical University	2
2	University of Sharjah	2
3	Aarhus University	1
4	Aarhus University Hospital	1
5	Adelaide University	1
6	Alexandria Higher Institute of Engineering and Technology	1
7	Alexandria University	1
8	Amsterdam University Medical Centers	1
9	Anglia Ruskin University	1
10	Arab Academy for Science, Technology, and Maritime Transport	1

Countries with the most papers, since 2023
#	Country	Papers
1	China	12
2	India	11
3	United Kingdom	6
4	Saudi Arabia	5
5	United States	5
6	United Arab Emirates	4
7	Australia	4
8	Bangladesh	2
9	Egypt	2
10	Netherlands	2

Keywords with the most papers, since 2023
#	Keyword	Papers
1	LIDC-IDRI	19
2	lung nodule classification	9
3	transfer learning	6
4	computer-aided diagnosis	5
5	convolutional neural networks	5
6	explainable AI	5
7	lung cancer detection	4
8	lung cancer screening	4
9	lung nodule segmentation	4
10	medical image segmentation	4

Most-cited papers#

Most-cited papers since 2017
#	Citations	Per month	Title	Journal	Published	Authors
1	286	2.6	Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT	Information Fusion	2017-10-25	Yutong Xie, Jianpeng Zhang, Yong Xia et al.
2	200	6.3	Foundation model for cancer imaging biomarkers	Nature Machine Intelligence	2024-03-15	Suraj Pai, Dennis Bontempi, Ibrahim Hadžić et al.
3	158	1.5	Multi-view multi-scale CNNs for lung nodule type classification from CT images	Pattern Recognition	2018-01-04	Xinglong Liu, Fei Hou, Hong Qin et al.
4	121	1.7	Learning efficient, explainable and discriminative representations for pulmonary nodules classification	Pattern Recognition	2021-01-14	Hanliang Jiang, Fuhao Shen, Fei Gao et al.
5	107	1.2	Automated 3-D lung tumor detection and classification by an active contour model and CNN classifier	Expert Systems with Applications	2019-05-27	Gopi Kasinathan, S. K. V. Jayakumar, Amir H. Gandomi et al.

Archive counts by publication year: a paper counts when its title, abstract or keywords name the dataset, or when OpenAlex's full-text search finds it there (searched for the last 30 days' papers and, by a pass over the past years, for older ones). Names added to the list later are looked for in older papers as the archive is read again.

Used together with#

Papers use LIDC-IDRI most often with ImageNet (12), Kaggle (7) and BraTS (6); it has 9 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST. The whole network →

What papers use LIDC-IDRI together with (at least 3 papers; lift 1 = chance)
Used with	Type	Papers using both	Lift
ImageNet	Dataset	12	3.7
Kaggle	Dataset	7	8.8
BraTS	Dataset	6	16.0
MNIST / Fashion-MNIST	Dataset	6	3.9
Chest X-ray (CheXpert, ChestX-ray14)	Dataset	5	37.8
ISIC skin lesion archive	Dataset	5	37.4
TCGA	Dataset	5	20.0
CIFAR-10 / CIFAR-100	Dataset	3	1.6
MIMIC	Dataset	3	6.4

Cite this page

Scholar4AI. (2026). LIDC-IDRI. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/lidc-idri

@misc{scholar4ai-datasets-lidc-idri,
  author = {{Scholar4AI}},
  title = {LIDC-IDRI},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/lidc-idri}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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