Peter Szolovits
About
In The Last Decade
Peter Szolovits
170 papers receiving 12.9k citations
Hit Papers
Peers
Comparison fields: 5 of 198
- Artificial Intelligence 7.0k
- Molecular Biology 2.6k
- Epidemiology 2.2k
- Health Information Management 2.1k
- Health Informatics 1.2k
Countries citing papers authored by Peter Szolovits
This map shows the geographic impact of Peter Szolovits'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 Peter Szolovits with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Szolovits more than expected).
Fields of papers citing papers by Peter Szolovits
This network shows the impact of papers produced by Peter Szolovits. 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 Peter Szolovits. The network helps show where Peter Szolovits may publish in the future.
Co-authorship network of co-authors of Peter Szolovits
This figure shows the co-authorship network connecting the top 25 collaborators of Peter Szolovits. A scholar is included among the top collaborators of Peter Szolovits 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 Peter Szolovits. Peter Szolovits is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 12 | |
| 2 | 0 | |
| 3 | 14 | |
| 4 | Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation | 1 |
| 5 | Is BERT Really Robust? Natural Language Attack on Text Classification and Entailment | 83 |
| 6 | 61 | |
| 7 | Continuous State-Space Models for Optimal Sepsis Treatment: a Deep Reinforcement Learning Approach. | 6 |
| 8 | Demonstrating the Advantages of Applying Data Mining Techniques on Time-Dependent Electronic Medical Records. | 4 |
| 9 | Unfolding physiological state: mortality modelling in intensive care units | 32 |
| 10 | Mortality and extraintestinal cancers in patients with primary sclerosing cholangitis and inflammatory bowel disease | 1 |
| 11 | 21 | |
| 12 | Multilingual Named-Entity Recognition from Parallel Corpora. | 1 |
| 13 | 168 | |
| 14 | Psychiatric co-morbidity is associated with increased risk of surgery in Crohn's disease | 1 |
| 15 | Association Between Reduced Plasma 25-Hydroxy Vitamin D and Increased Risk of Cancer in Patients With Inflammatory Bowel Diseases | 4 |
| 16 | Improving Case Definition of Crohnʼs Disease and Ulcerative Colitis in Electronic Medical Records Using Natural Language Processing | 2 |
| 17 | Normalization of Plasma 25-Hydroxy Vitamin D Is Associated with Reduced Risk of Surgery in Crohn’s Disease | 9 |
| 18 | I-in-a-Box: A Knowledge-Based System for Space Science Experimentation | 1 |
| 19 | Information acquisition in diagnosis | 11 |
| 20 | Brand X: LISP support for semantic networks | 2 |
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.