Ahmed Salih

1.6k citations
41 papers · 567 indexed · 1 hit paper · h-index 11
Topics
Artificial Intelligence in Healthcare and Education (11 papers)Machine Learning in Healthcare (8 papers)Explainable Artificial Intelligence (XAI) (8 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
Partner nations
United KingdomItalyIraq

In The Last Decade

Ahmed Salih

36 papers receiving 552 citations

Hit Papers

A Perspective on Explainable Artificial Intelligence Meth...202420262025202450100150

Peers

Ahmed Salih
Comparison fields: 5 of 140
  • Artificial Intelligence 127
  • Radiology, Nuclear Medicine and Imaging 100
  • Cardiology and Cardiovascular Medicine 93
  • Health Informatics 71
  • Infectious Diseases 59
Replace Heewon Chung with:
Heewon Chung South Korea
Guy Handelman Ireland
Junhong Chen China
Nadia Antonucci Italy
Daniel S. Herman United States
Hema Sekhar Reddy Rajula Italy
Raphaël Couronné France
Koutarou Matsumoto Japan
Vajira Thambawita Norway
Ahmed Salih relative to Heewon Chung South Korea Heewon Chung's profile →
Citations per field
00.5×10×15×
Heewon Chung · 1×
Citations per year

Countries citing papers authored by Ahmed Salih

Since Specialization
Citations

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

Fields of papers citing papers by Ahmed Salih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ahmed Salih

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 3
4 2
5 0
6 2
7 16
8 10
9 9
10 3
11 3
12 0
13
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIMEbreakdown →
199
14 10
15 3
16 11
17 12
18 3
19 20
20 2

About Ahmed Salih

Ahmed Salih is a scholar working on Health Informatics, Aging and Radiology, Nuclear Medicine and Imaging, having authored 41 papers that have together received 567 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (11 papers), Machine Learning in Healthcare (8 papers) and Explainable Artificial Intelligence (XAI) (8 papers). The work is most often cited by research in Health Informatics (71 citations), Aging (9 citations) and Health Information Management (20 citations). Ahmed Salih has collaborated with scholars based in United Kingdom, Italy and Iraq. Frequent co-authors include Steffen E. Petersen, Zahra Raisi‐Estabragh, Ilaria Boscolo Galazzo, Karim Lekadir, Petia Radeva, Gloria Menegaz, Aaron M. Lee, Polyxeni Gkontra, Nicholas C. Harvey and Stefan Neubauer. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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