Khalid Gaffer Mohamed

1.0k total citations · 1 hit paper
9 papers, 587 citations indexed

About

Khalid Gaffer Mohamed is a scholar working on General Health Professions, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Khalid Gaffer Mohamed has authored 9 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in General Health Professions, 3 papers in Artificial Intelligence and 2 papers in Health Information Management. Recurrent topics in Khalid Gaffer Mohamed's work include Primary Care and Health Outcomes (4 papers), Healthcare Policy and Management (2 papers) and Image and Signal Denoising Methods (2 papers). Khalid Gaffer Mohamed is often cited by papers focused on Primary Care and Health Outcomes (4 papers), Healthcare Policy and Management (2 papers) and Image and Signal Denoising Methods (2 papers). Khalid Gaffer Mohamed collaborates with scholars based in Saudi Arabia, Sudan and Norway. Khalid Gaffer Mohamed's co-authors include Saman Zeeshan, XinQi Dong, Zeeshan Ahmed, Elfatih M Malik, Steinar Hunskaar, Emad A. Mohamed, S. El-Debeiky, Hani Atwa, M.M. Mansour and Mohamed Hany Shehata and has published in prestigious journals such as SHILAP Revista de lepidopterología, International Journal of Electrical Power & Energy Systems and PeerJ.

In The Last Decade

Khalid Gaffer Mohamed

9 papers receiving 548 citations

Hit Papers

Artificial intelligence with multi-functional machine lea... 2020 2026 2022 2024 2020 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine
    2020 524 citations Zeeshan Ahmed, Khalid Gaffer Mohamed et al. Database profile →

Peers

Khalid Gaffer Mohamed
Abhimanyu S. Ahuja United States
Beau Norgeot United States
Saurabh Johri United Kingdom
Sarah Enslin United States
Lama Moukheiber United States
Junaid Bajwa United Kingdom
Mehmet Aydar United States
Colin B. Compas United States
Usman Munir United States
Dennis Shung United States
Abhimanyu S. Ahuja United States
Khalid Gaffer Mohamed
Citations per year, relative to Khalid Gaffer Mohamed Khalid Gaffer Mohamed (= 1×) peers Abhimanyu S. Ahuja

Countries citing papers authored by Khalid Gaffer Mohamed

Since Specialization
Citations

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

Fields of papers citing papers by Khalid Gaffer Mohamed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khalid Gaffer Mohamed. 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 Khalid Gaffer Mohamed. The network helps show where Khalid Gaffer Mohamed may publish in the future.

Co-authorship network of co-authors of Khalid Gaffer Mohamed

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

All Works

9 of 9 papers shown
1.
2.
Mohamed, Khalid Gaffer, et al.. (2021). The Effect of Public Health Measures during the COVID-19 Pandemic on Smoking Dependence & Passive Smoking. Journal of Pharmaceutical Research International. 167–180. 1 indexed citations
3.
Ahmed, Zeeshan, Khalid Gaffer Mohamed, Saman Zeeshan, & XinQi Dong. (2020). Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database. 2020. 524 indexed citations breakdown →
4.
Mohamed, Khalid Gaffer, et al.. (2019). Impact on core values of family medicine from a 2-year Master’s programme in Gezira, Sudan: observational study. BMC Family Practice. 20(1). 145–145. 7 indexed citations
5.
Mohamed, Khalid Gaffer, et al.. (2017). Confidence in Procedural Skills before and after a Two-Year Master’s Programme in Family Medicine in Gezira State, Sudan. SHILAP Revista de lepidopterología. 2017. 1–11. 6 indexed citations
6.
Mohamed, Khalid Gaffer, et al.. (2015). Telemedicine and E-Learning in a Primary Care Setting in Sudan: The Experience of the Gezira Family Medicine Project. SHILAP Revista de lepidopterología. 2015. 1–7. 10 indexed citations
7.
8.
Mohamed, Emad A., M.M. Mansour, S. El-Debeiky, Khalid Gaffer Mohamed, & N.D. Rao. (2002). Egyptian Unified Grid hourly load forecasting using artificial neural network. 1. 366–369. 2 indexed citations
9.
Mohamed, Emad A., et al.. (1998). Egyptian Unified Grid hourly load forecasting using artificial neural network. International Journal of Electrical Power & Energy Systems. 20(7). 495–500. 8 indexed citations

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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