Muhammad Umer

4.5k citations
118 papers · 2.9k · 2 hit papers · h-index 32

Impact in

Papers in

Muhammad Umer

111 papers receiving 2.8k citations

Muhammad Umer's Hit Papers

Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques 2021 · 281 citations
2810+2+4Years since publication50100150200250

Peers

Muhammad Umer
Comparison fields: 5 of 158
  • Health Information Management 290
  • Health Informatics 57
  • Artificial Intelligence 1.2k
  • Information Systems 511
  • Signal Processing 245
Replace Furqan Rustam with:
Furqan Rustam South Korea
Sushruta Mishra India
Arif Mehmood Pakistan
Saleem Ullah Pakistan
Mohammad Shahadat Hossain Bangladesh
Aditya Khamparia India
Tarik A. Rashid Iraq
Mamta Mittal India
Atta Rahman Saudi Arabia
M. F. Mridha Bangladesh
Muhammad Umer relative to Furqan Rustam South Korea Furqan Rustam's profile →
Citations per field
00.5×1.5×
Furqan Rustam · 1×
Citations per year

Countries citing papers authored by Muhammad Umer

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Umer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Muhammad Umer, 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 Muhammad Umer Line = papers co-authored together Muhammad Umer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 118 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques
Hit paper breakdown →
2021281
2
Fake News Stance Detection Using Deep Learning Architecture (CNN-LSTM)
Hit paper breakdown →
2020224
3 2022101
4 202297
5 202091
6 202286
7 202184
8 202082
9 202179
10 202179
11 202167
12 202067
13 202059
14 201957
15 202253
16 202250
17 202150
18 202249
19 202046
20 202343

About Muhammad Umer

Muhammad Umer is a scholar working on Artificial Intelligence, Information Systems, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Health Information Management, having authored 118 papers that have together received 2.9k indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Artificial Intelligence in Healthcare (15 papers), Sentiment Analysis and Opinion Mining (14 papers), COVID-19 diagnosis using AI (13 papers), Advanced Malware Detection Techniques (9 papers), Misinformation and Its Impacts (8 papers), Advanced Text Analysis Techniques (8 papers) and Spam and Phishing Detection (8 papers). The work is most often cited by research in Health Information Management (290 citations), Health Informatics (57 citations), Artificial Intelligence (1.2k citations), Information Systems (511 citations) and Signal Processing (245 citations). Muhammad Umer has collaborated with scholars based in Pakistan, Saudi Arabia and South Korea. Frequent co-authors include Saima Sadiq, Saleem Ullah, Michele Nappi, Imran Ashraf, Arif Mehmood, Gyu Sang Choi, Abid Ishaq, Seyedali Mirjalili, Vaibhav Rupapara and Zainab Imtiaz. Their work appears in journals such as IEEE Access, Multimedia Tools and Applications, PeerJ Computer Science, Image and Vision Computing and PLoS ONE.

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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