Isabella Nogues
- Radiology, Nuclear Medicine and Imaging top 0.5%
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Biomedical Engineering top 10%
- Pulmonary and Respiratory Medicine top 5%
- Co-authors
- Le LüZiyue XuDaniel J. MolluraRonald M. SummersMingchen GaoHolger R. RothHoo-Chang ShinJianhua Yao
- Topics
- Radiomics and Machine Learning in Medical Imaging (3 papers)Lung Cancer Diagnosis and Treatment (3 papers)Pancreatic and Hepatic Oncology Research (1 paper)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingComputer Vision and Pattern Recognition
- Partner nations
- United StatesChinaMalaysia
In The Last Decade
Isabella Nogues
6 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Radiology, Nuclear Medicine and Imaging 1.5k
- Artificial Intelligence 1.5k
- Computer Vision and Pattern Recognition 1.1k
- Biomedical Engineering 460
- Pulmonary and Respiratory Medicine 442
Countries citing papers authored by Isabella Nogues
This map shows the geographic impact of Isabella Nogues's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Isabella Nogues with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Isabella Nogues more than expected).
Fields of papers citing papers by Isabella Nogues
This network shows the impact of papers produced by Isabella Nogues. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Isabella Nogues. The network helps show where Isabella Nogues may publish in the future.
Co-authorship network of co-authors of Isabella Nogues
This figure shows the co-authorship network connecting the top 25 collaborators of Isabella Nogues. A scholar is included among the top collaborators of Isabella Nogues based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Isabella Nogues. Isabella Nogues is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 36 | |
| 2 | 27 | |
| 3 | Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learningbreakdown → | 3968 |
| 4 | 3 | |
| 5 | 26 | |
| 6 | 3 |
About Isabella Nogues
Isabella Nogues is a scholar working on Otorhinolaryngology, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 6 papers that have together received 4.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Lung Cancer Diagnosis and Treatment (3 papers) and Pancreatic and Hepatic Oncology Research (1 paper). The work is most often cited by research in Health Informatics (103 citations), Radiology, Nuclear Medicine and Imaging (1.5k citations) and Computer Vision and Pattern Recognition (1.1k citations). Isabella Nogues has collaborated with scholars based in United States, China and Malaysia. Frequent co-authors include Le Lü, Ziyue Xu, Daniel J. Mollura, Ronald M. Summers, Mingchen Gao, Holger R. Roth, Hoo-Chang Shin, Jianhua Yao, Ling Zhang and Jiawen Yao. Their work appears in journals such as Clinical Cancer Research, IEEE Transactions on Medical Imaging and AJOB Empirical Bioethics.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.