Joana Morgado

676 citations
15 papers · 354 indexed · h-index 10
Topics
Radiomics and Machine Learning in Medical Imaging (7 papers)Lung Cancer Diagnosis and Treatment (7 papers)AI in cancer detection (7 papers)
Journals
SHILAP Revista de lepidopterologíaGreen ChemistryExpert Systems with Applications

In The Last Decade

Joana Morgado

15 papers receiving 333 citations

Peers

Joana Morgado
Comparison fields: 5 of 83
  • Radiology, Nuclear Medicine and Imaging 117
  • Epidemiology 88
  • Artificial Intelligence 80
  • Pulmonary and Respiratory Medicine 77
  • Infectious Diseases 51
Replace Fiona Ryan with:
Fiona Ryan United States
Hassan Aboul-Ella Egypt
Cheng Ge China
Yongping Lin China
K. S. Swathi India
Yusuke Nomura Japan
Shafiq Ur Rehman Pakistan
Soon Bin Kwon South Korea
Abdullahi Umar Ibrahim Cyprus
Tommy Liu United States
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Citations per field
00.5×5.7×
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Citations per year

Countries citing papers authored by Joana Morgado

Since Specialization
Citations

This map shows the geographic impact of Joana Morgado'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 Joana Morgado with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joana Morgado more than expected).

Fields of papers citing papers by Joana Morgado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joana Morgado. 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 Joana Morgado. The network helps show where Joana Morgado may publish in the future.

Co-authorship network of co-authors of Joana Morgado

This figure shows the co-authorship network connecting the top 25 collaborators of Joana Morgado. A scholar is included among the top collaborators of Joana Morgado 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 Joana Morgado. Joana Morgado is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 26
2 32
3 6
4 31
5 27
6 2
7 5
8 29
9 18
10 68
11 33
12 26
13 43
14 1
15 7

About Joana Morgado

Joana Morgado is a scholar working on Health Informatics, Energy Engineering and Power Technology and Radiology, Nuclear Medicine and Imaging, having authored 15 papers that have together received 354 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), Lung Cancer Diagnosis and Treatment (7 papers) and AI in cancer detection (7 papers). The work is most often cited by research in Health Informatics (21 citations), Radiology, Nuclear Medicine and Imaging (117 citations) and Agronomy and Crop Science (49 citations). Joana Morgado has collaborated with scholars based in Portugal, United States and Switzerland. Frequent co-authors include Francisco Silva, Hélder P. Oliveira, Tânia Pereira, A. Cunha, Cláudia Freitas, Isabel Ramos, José Luís Costa, António J. Madureira, Venceslau Hespanhol and Preben Willeberg. Their work appears in journals such as SHILAP Revista de lepidopterología, Green Chemistry and Expert Systems with Applications.

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.

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