Mohammad Rahimzadeh

428 citations
3 papers · 195 indexed · 1 hit paper · h-index 3
Co-authors
E. Safi
Topics
Radiomics and Machine Learning in Medical Imaging (1 paper)Advanced Image and Video Retrieval Techniques (1 paper)Smart Agriculture and AI (1 paper)
Partner nations
Iran

In The Last Decade

Mohammad Rahimzadeh

3 papers receiving 188 citations

Hit Papers

A fully automated deep learning-based network for detecti...2021202620222024202150100150

Peers

Mohammad Rahimzadeh
Comparison fields: 5 of 29
  • Radiology, Nuclear Medicine and Imaging 178
  • Artificial Intelligence 115
  • Health Informatics 40
  • Pulmonary and Respiratory Medicine 27
  • Computer Vision and Pattern Recognition 26
Replace Iván Sevillano-García with:
Iván Sevillano-García Spain
Shahin Heidarian Canada
Polycarp Shizawaliyi Yakoi China
Erdi Çallı Netherlands
Enzo Tartaglione France
Asmaa Abbas Egypt
Emanuele Pesce United Kingdom
Dandan Tu China
Mehak Aggarwal India
Mohammad Rahimzadeh relative to Iván Sevillano-García Spain Iván Sevillano-García's profile →
Citations per field
00.5×1.6×
Iván Sevillano-García · 1×
Citations per year

Countries citing papers authored by Mohammad Rahimzadeh

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Rahimzadeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mohammad Rahimzadeh

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

All Works

3 of 3 papers shown
#WorkIndexed citations
1 2
2
A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan datasetbreakdown →
190
3
Introduction of a new Dataset and Method for Detecting and Counting the Pistachios based on Deep Learning.
3

About Mohammad Rahimzadeh

Mohammad Rahimzadeh is a scholar working on Nutrition and Dietetics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 3 papers that have together received 195 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (1 paper), Advanced Image and Video Retrieval Techniques (1 paper) and Smart Agriculture and AI (1 paper). The work is most often cited by research in Health Informatics (40 citations), Radiology, Nuclear Medicine and Imaging (178 citations) and Artificial Intelligence (115 citations). Mohammad Rahimzadeh has collaborated with scholars based in Iran. Frequent co-authors include E. Safi. Their work appears in journals such as Biomedical Signal Processing and Control and Pattern Analysis and 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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