Subramani Mani
- Artificial Intelligence top 2%
- Molecular Biology
- Psychiatry and Mental health top 10%
- Pediatrics, Perinatology and Child Health top 10%
- Health Information Management top 1%
- Co-authors
- Constantin AliferisYukun ChenAlexander StatnikovXenofon KoutsoukosIoannis TsamardinosSuzanne McDermottJoshua C. DennyHua Xu
- Topics
- Bayesian Modeling and Causal Inference (12 papers)Biomedical Text Mining and Ontologies (10 papers)Machine Learning in Healthcare (5 papers)
- Partner nations
- United StatesGreeceNetherlands
In The Last Decade
Subramani Mani
35 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 143
- Artificial Intelligence 783
- Molecular Biology 415
- Psychiatry and Mental health 175
- Pediatrics, Perinatology and Child Health 160
- Health Information Management 153
Countries citing papers authored by Subramani Mani
This map shows the geographic impact of Subramani Mani'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 Subramani Mani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subramani Mani more than expected).
Fields of papers citing papers by Subramani Mani
This network shows the impact of papers produced by Subramani Mani. 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 Subramani Mani. The network helps show where Subramani Mani may publish in the future.
Co-authorship network of co-authors of Subramani Mani
This figure shows the co-authorship network connecting the top 25 collaborators of Subramani Mani. A scholar is included among the top collaborators of Subramani Mani 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 Subramani Mani. Subramani Mani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 40 | |
| 4 | 140 | |
| 5 | 214 | |
| 6 | Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing | 8 |
| 7 | 33 | |
| 8 | 309 | |
| 9 | 106 | |
| 10 | Early prediction of reading disability using machine learning. | 6 |
| 11 | Bayesian Algorithms for Causal Data Mining | 6 |
| 12 | A theoretical study of Y structures for causal discovery | 24 |
| 13 | A Simulation Study of Three Related Causal Data Mining Algorithms | 8 |
| 14 | Causal discovery from medical textual data. | 16 |
| 15 | 13 | |
| 16 | When the interface is a face | 6 |
| 17 | Beyond concise and colorful: learning intelligible rules | 31 |
| 18 | Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach | 7 |
| 19 | 17 | |
| 20 | 75 |
About Subramani Mani
Subramani Mani is a scholar working on Artificial Intelligence, Health Information Management and Management Science and Operations Research, having authored 36 papers that have together received 1.5k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (12 papers), Biomedical Text Mining and Ontologies (10 papers) and Machine Learning in Healthcare (5 papers). The work is most often cited by research in Health Information Management (153 citations), Health Informatics (38 citations) and Artificial Intelligence (783 citations). Subramani Mani has collaborated with scholars based in United States, Greece and Netherlands. Frequent co-authors include Constantin Aliferis, Yukun Chen, Alexander Statnikov, Xenofon Koutsoukos, Ioannis Tsamardinos, Suzanne McDermott, Joshua C. Denny, Hua Xu, Gregory F. Cooper and S. Trent Rosenbloom. Their work appears in journals such as Bioinformatics, BMC Bioinformatics and Journal of the American Medical Informatics Association.
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.