Muddasar Naeem

1.1k citations
27 papers · 598 · 1 hit paper · h-index 12

Impact in

Papers in

Muddasar Naeem

25 papers receiving 576 citations

Muddasar Naeem's Hit Papers

Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends 2024 · 42 citations
420+1Years since publication10203040

Peers

Muddasar Naeem
Comparison fields: 5 of 112
  • Health Informatics 56
  • Family Practice 18
  • Health Information Management 36
  • Artificial Intelligence 221
  • Geriatrics and Gerontology 16
Replace Giovanni Paragliola with:
Giovanni Paragliola Italy
Nora El-Rashidy Egypt
Zhicheng Cui United States
Ali Raza Pakistan
Zahra Shakeri Hossein Abad Canada
David McSherry United Kingdom
Reza Samavi Canada
José-Francisco Díez-Pastor Spain
Nancy Victor India
Ayush Goyal India
Muddasar Naeem relative to Giovanni Paragliola Italy Giovanni Paragliola's profile →
Citations per field
00.5×
Giovanni Paragliola · 1×
Citations per year

Countries citing papers authored by Muddasar Naeem

Since Specialization
Citations

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

Fields of papers citing papers by Muddasar Naeem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Muddasar Naeem, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muddasar Naeem Line = papers co-authored together Muddasar Naeem links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020182
2 2020131
3 202355
4
Impact of AI-Powered Solutions in Rehabilitation Process: Recent Improvements and Future Trends
Hit paper breakdown →
202442
5 202127
6 202027
7 202214
8 202213
9 201912
10 201912
11 202211
12 202311
13 201910
14 20209
15 20228
16 20188
17 20165
18 20154
19 20243
20 20213

About Muddasar Naeem

Muddasar Naeem is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering, Computer Networks and Communications, Cognitive Neuroscience and Geriatrics and Gerontology, having authored 27 papers that have together received 598 indexed citations. Recurring topics across this work include Advanced MIMO Systems Optimization (7 papers), Machine Learning in Healthcare (6 papers), EEG and Brain-Computer Interfaces (5 papers), Pharmaceutical Practices and Patient Outcomes (4 papers), Advanced Wireless Network Optimization (4 papers), Reinforcement Learning in Robotics (4 papers), Cooperative Communication and Network Coding (4 papers) and COVID-19 diagnosis using AI (3 papers). The work is most often cited by research in Health Informatics (56 citations), Family Practice (18 citations), Health Information Management (36 citations), Artificial Intelligence (221 citations) and Geriatrics and Gerontology (16 citations). Muddasar Naeem has collaborated with scholars based in Italy, Pakistan and Netherlands. Frequent co-authors include Antonio Coronato, Giuseppe De Pietro, Giovanni Paragliola, Syed Tahir Hussain Rizvi, Zaib Ullah, Patrizia Ribino, Fabrizio Stasolla, Sajid Bashir, Mario Ciampi and Stefano Silvestri. Their work appears in journals such as Expert Systems with Applications, Journal of Reliable Intelligent Environments, Sensors, IEEE Access and Future Internet.

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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