Ioana Bica
- Infectious Diseases top 2%
- Epidemiology top 5%
- Hepatology top 1%
- Emergency Medicine top 5%
- Molecular Biology
- Co-authors
- David R. SnydmanMihaela van der SchaarK. McGowanBarbara McGovernRavi DharRochelle ScheibDavid StoneAri Ercole
- Topics
- Liver Disease Diagnosis and Treatment (5 papers)Advanced Causal Inference Techniques (5 papers)Hepatitis C virus research (5 papers)
- Partner nations
- United StatesUnited KingdomBrazil
In The Last Decade
Ioana Bica
29 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Infectious Diseases 729
- Epidemiology 720
- Hepatology 700
- Emergency Medicine 151
- Molecular Biology 133
Countries citing papers authored by Ioana Bica
This map shows the geographic impact of Ioana Bica'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 Ioana Bica with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioana Bica more than expected).
Fields of papers citing papers by Ioana Bica
This network shows the impact of papers produced by Ioana Bica. 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 Ioana Bica. The network helps show where Ioana Bica may publish in the future.
Co-authorship network of co-authors of Ioana Bica
This figure shows the co-authorship network connecting the top 25 collaborators of Ioana Bica. A scholar is included among the top collaborators of Ioana Bica 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 Ioana Bica. Ioana Bica is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 25 | |
| 4 | SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes | 6 |
| 5 | 25 | |
| 6 | OrganITE: Optimal transplant donor organ offering using an individual treatment effect | 5 |
| 7 | Strictly Batch Imitation Learning by Energy-based Distribution Matching | 0 |
| 8 | Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making. | 1 |
| 9 | 368 | |
| 10 | 12 | |
| 11 | Multi-omics data integration using cross-modal neural networks. | 5 |
| 12 | 1 | |
| 13 | 25 | |
| 14 | 5 | |
| 15 | 33 | |
| 16 | 219 | |
| 17 | 36 | |
| 18 | 11 | |
| 19 | Increasing Mortality Due to End-Stage Liver Disease in Patients with Human Immunodeficiency Virus Infectionbreakdown → | 775 |
| 20 | 1 |
About Ioana Bica
Ioana Bica is a scholar working on Hepatology, Modeling and Simulation and Statistics and Probability, having authored 31 papers that have together received 1.8k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (5 papers), Advanced Causal Inference Techniques (5 papers) and Hepatitis C virus research (5 papers). The work is most often cited by research in Hepatology (700 citations), Infectious Diseases (729 citations) and Virology (104 citations). Ioana Bica has collaborated with scholars based in United States, United Kingdom and Brazil. Frequent co-authors include David R. Snydman, Mihaela van der Schaar, K. McGowan, Barbara McGovern, Ravi Dhar, Rochelle Scheib, David Stone, Ari Ercole, P. O. Baqui and Valerio Marra. Their work appears in journals such as Bioinformatics, Neurology and Clinical Infectious Diseases.
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.