Saima Sadiq

40 papers receiving 1.3k citations

Saima Sadiq's Hit Papers

Improving the Prediction of Heart Failure Patients’ Survival Using SMOTE and Effective Data Mining Techniques 2021 · 255 citations
2550+1+3Years since publication50100150200250

Peers

Saima Sadiq
Comparison fields: 5 of 132
  • Health Information Management 217
  • Health Informatics 27
  • Artificial Intelligence 583
  • Radiology, Nuclear Medicine and Imaging 194
  • Signal Processing 100
Replace T R Mahesh with:
T R Mahesh India
Mohammad Shahadat Hossain Bangladesh
Umesh Kumar Lilhore India
Hassan Al Moatassime Morocco
Amjad Ali Pakistan
Sushruta Mishra India
Ramesh Chandra Poonia India
Atta Rahman Saudi Arabia
Vicente García‐Díaz Spain
Mirjam Jonkman Australia
Saima Sadiq relative to T R Mahesh India T R Mahesh's profile →
Citations per field
00.5×7.2×
T R Mahesh · 1×
Citations per year

Countries citing papers authored by Saima Sadiq

Since Specialization
Citations

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

Fields of papers citing papers by Saima Sadiq

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 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 →
2021255
2 202099
3 202298
4 202176
5 202076
6 202075
7 202169
8 202166
9 202253
10 202148
11 202246
12 202244
13 202242
14 202239
15 202136
16 201332
17 202226
18 202123
19 202322
20 202220

About Saima Sadiq

Saima Sadiq is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Sociology and Political Science and Radiology, Nuclear Medicine and Imaging, having authored 42 papers that have together received 1.4k indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (7 papers), Spam and Phishing Detection (6 papers), COVID-19 diagnosis using AI (6 papers), Misinformation and Its Impacts (5 papers), Advanced Malware Detection Techniques (4 papers), Artificial Intelligence in Healthcare (3 papers), IoT and Edge/Fog Computing (3 papers) and AI in cancer detection (3 papers). The work is most often cited by research in Health Information Management (217 citations), Health Informatics (27 citations), Artificial Intelligence (583 citations), Radiology, Nuclear Medicine and Imaging (194 citations) and Signal Processing (100 citations). Saima Sadiq has collaborated with scholars based in Pakistan, South Korea and Italy. Frequent co-authors include Muhammad Umer, Saleem Ullah, Michele Nappi, Seyedali Mirjalili, Vaibhav Rupapara, Abid Ishaq, Imran Ashraf, Ala’ Abdulmajid Eshmawi, Gyu Sang Choi and Arif Mehmood. Their work appears in journals such as IEEE Access, PeerJ Computer Science, Electronics, Computers, materials & continua/Computers, materials & continua (Print) and Sensors.

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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