Daniel Ramirez-Cano
Impact in
- Health top 5%
- Social Media in Health Education
- General Health Professions top 5%
- Patient Satisfaction in Healthcare
- Health Literacy and Information Accessibility
- Patient-Provider Communication in Healthcare
Papers in
-
- Patient Satisfaction in Healthcare 3
- Co-authors
- Ara Darzi (5 shared papers)Felix Greaves (5 shared papers)Christopher Millett (4 shared papers)Liam Donaldson (3 shared papers)Jeremy Pitt (4 shared papers)Dominic King (1 shared paper)Ivo Vlaev (1 shared paper)Simon Colton (1 shared paper)
- Journals
- BMJ Quality & Safety (2 papers)Health Policy (1 paper)Journal of Medical Internet Research (1 paper)Computational and Mathematical Organization Theory (1 paper)The Lancet (1 paper)
- Partner nations
- United KingdomUnited StatesGreece
In The Last Decade
Daniel Ramirez-Cano
10 papers receiving 598 citations
Daniel Ramirez-Cano's Hit Papers
Peers
Comparison fields: 5 of 89
- Health 89
- General Health Professions 157
- Health Information Management 26
- Artificial Intelligence 157
- Health Informatics 6
Countries citing papers authored by Daniel Ramirez-Cano
This map shows the geographic impact of Daniel Ramirez-Cano'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 Daniel Ramirez-Cano with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Ramirez-Cano more than expected).
Fields of papers citing papers by Daniel Ramirez-Cano
This network shows the impact of papers produced by Daniel Ramirez-Cano. 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 Daniel Ramirez-Cano. The network helps show where Daniel Ramirez-Cano may publish in the future.
Co-authors
The 13 scholars most cited alongside Daniel Ramirez-Cano, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Use of Sentiment Analysis for Capturing Patient Experience From Free-Text Comments Posted Online Hit paper breakdown → | 2013 | 245 |
| 2 | 2013 | 207 | |
| 3 | 2013 | 74 | |
| 4 | 2006 | 32 | |
| 5 | 2010 | 19 | |
| 6 | 2011 | 14 | |
| 7 | 2012 | 14 | |
| 8 | 2008 | 9 | |
| 9 | 2014 | 5 | |
| 10 | 2005 | 2 |
About Daniel Ramirez-Cano
Daniel Ramirez-Cano is a scholar working on General Health Professions, Sociology and Political Science, Statistical and Nonlinear Physics, Artificial Intelligence and Health, having authored 10 papers that have together received 621 indexed citations. Recurring topics across this work include Patient Satisfaction in Healthcare (3 papers), Opinion Dynamics and Social Influence (3 papers), Multi-Agent Systems and Negotiation (2 papers), Healthcare Policy and Management (2 papers), Complex Network Analysis Techniques (2 papers), Social Media in Health Education (2 papers), Artificial Intelligence in Games (1 paper) and Translation Studies and Practices (1 paper). The work is most often cited by research in Health (89 citations), General Health Professions (157 citations), Health Information Management (26 citations), Artificial Intelligence (157 citations) and Health Informatics (6 citations). Daniel Ramirez-Cano has collaborated with scholars based in United Kingdom, United States and Greece. Frequent co-authors include Ara Darzi, Felix Greaves, Christopher Millett, Liam Donaldson, Jeremy Pitt, Dominic King, Ivo Vlaev, Simon Colton, Robin Baumgarten and Alexander Artikis. Their work appears in journals such as BMJ Quality & Safety, Health Policy, Journal of Medical Internet Research, Computational and Mathematical Organization Theory and The Lancet.
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.