Zuherman Rustam
Impact in
- Health Information Management top 0.2%
- Artificial Intelligence in Healthcare
- Artificial Intelligence top 2%
- AI in cancer detection
- Imbalanced Data Classification Techniques
Papers in
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- AI in cancer detection 39
- Imbalanced Data Classification Techniques 21
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- Artificial Intelligence in Healthcare 45
- Co-authors
- Jacub Pandelaki (25 shared papers)Titin Siswantining (9 shared papers)Devvi Sarwinda (5 shared papers)Rahmat Hidayat (6 shared papers)Stéphane Cédric Koumetio Tekouabou (1 shared paper)El Arbi Abdellaoui Alaoui (1 shared paper)Dipo Aldila (1 shared paper)María Jesús Segovia Vargas (1 shared paper)
In The Last Decade
Zuherman Rustam
136 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 139
- Health Information Management 344
- Artificial Intelligence 696
- Neurology 87
- Health Informatics 14
- Computer Vision and Pattern Recognition 197
Countries citing papers authored by Zuherman Rustam
This map shows the geographic impact of Zuherman Rustam'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 Zuherman Rustam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zuherman Rustam more than expected).
Fields of papers citing papers by Zuherman Rustam
This network shows the impact of papers produced by Zuherman Rustam. 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 Zuherman Rustam. The network helps show where Zuherman Rustam may publish in the future.
Co-authors
The 25 scholars most cited alongside Zuherman Rustam, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 147 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 74 | |
| 2 | 2019 | 72 | |
| 3 | 2020 | 51 | |
| 4 | 2018 | 33 | |
| 5 | 2018 | 31 | |
| 6 | 2021 | 29 | |
| 7 | 2018 | 28 | |
| 8 | 2019 | 28 | |
| 9 | 2019 | 27 | |
| 10 | 2017 | 27 | |
| 11 | 2019 | 26 | |
| 12 | 2018 | 26 | |
| 13 | 2018 | 26 | |
| 14 | 2019 | 25 | |
| 15 | 2019 | 25 | |
| 16 | 2020 | 24 | |
| 17 | 2019 | 23 | |
| 18 | 2020 | 23 | |
| 19 | 2018 | 22 | |
| 20 | 2016 | 21 |
About Zuherman Rustam
Zuherman Rustam is a scholar working on Artificial Intelligence, Health Information Management, Computer Vision and Pattern Recognition, Molecular Biology and Information Systems, having authored 147 papers that have together received 1.4k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (45 papers), AI in cancer detection (39 papers), Data Mining and Machine Learning Applications (23 papers), Imbalanced Data Classification Techniques (21 papers), Gene expression and cancer classification (21 papers), Machine Learning in Bioinformatics (20 papers), Face and Expression Recognition (18 papers) and COVID-19 diagnosis using AI (12 papers). The work is most often cited by research in Health Information Management (344 citations), Artificial Intelligence (696 citations), Neurology (87 citations), Health Informatics (14 citations) and Computer Vision and Pattern Recognition (197 citations). Zuherman Rustam has collaborated with scholars based in Indonesia, Canada and Morocco. Frequent co-authors include Jacub Pandelaki, Titin Siswantining, Devvi Sarwinda, Rahmat Hidayat, Stéphane Cédric Koumetio Tekouabou, El Arbi Abdellaoui Alaoui, Dipo Aldila, María Jesús Segovia Vargas, Benyamin Kusumoputro and Hamidah Hamidah. Their work appears in journals such as Ophthalmology Retina, International Journal on Advanced Science Engineering and Information Technology, Big Data Mining and Analytics, Ophthalmic Research and Symmetry.
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.