Raffaele Rasoini

1.1k total citations · 1 hit paper
8 papers, 715 citations indexed

About

Raffaele Rasoini is a scholar working on Surgery, Cardiology and Cardiovascular Medicine and Health Information Management. According to data from OpenAlex, Raffaele Rasoini has authored 8 papers receiving a total of 715 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Surgery, 2 papers in Cardiology and Cardiovascular Medicine and 2 papers in Health Information Management. Recurrent topics in Raffaele Rasoini's work include Electronic Health Records Systems (2 papers), Cardiac pacing and defibrillation studies (1 paper) and Machine Learning in Healthcare (1 paper). Raffaele Rasoini is often cited by papers focused on Electronic Health Records Systems (2 papers), Cardiac pacing and defibrillation studies (1 paper) and Machine Learning in Healthcare (1 paper). Raffaele Rasoini collaborates with scholars based in Italy and United Kingdom. Raffaele Rasoini's co-authors include Gian Franco Gensini, Federico Cabitza, M Mazzanti, Giancarlo Casolo, Angela Locoro, Pedro Berjano, Giuseppe Ambrosio, Sabina Caciolli, Rosanna Abbate and Serafina Valente and has published in prestigious journals such as JAMA, Internal and Emergency Medicine and Health Informatics Journal.

In The Last Decade

Raffaele Rasoini

7 papers receiving 688 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Unintended Consequences of Machine Learning in Medicine

2017 604 citations Federico Cabitza, Raffaele Rasoini et al. JAMA profile →

Peers

Raffaele Rasoini

HI

AI

RNMI

CCM

HIM

Steven W J Nijman Netherlands

D. Douglas Miller United States

Selen Bozkurt Türkiye

Paras Malik India

Heather Mattie United States

Christopher A. Lovejoy United Kingdom

Sonoo Thadaney-Israni United States

Beau Norgeot United States

Joseph Futoma United States

David C. Kale United States

Steven W J Nijman Netherlands

Raffaele Rasoini

276 ×1.1

HI

304 ×1.4

AI

157 ×1.0

RNMI

79 ×0.8

CCM

107 ×1.1

HIM

Citations per year, relative to Raffaele Rasoini Raffaele Rasoini (= 1×) peers Steven W J Nijman

Countries citing papers authored by Raffaele Rasoini

Since Specialization

Citations

This map shows the geographic impact of Raffaele Rasoini'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 Raffaele Rasoini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raffaele Rasoini more than expected).

Fields of papers citing papers by Raffaele Rasoini

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raffaele Rasoini. 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 Raffaele Rasoini. The network helps show where Raffaele Rasoini may publish in the future.

Co-authorship network of co-authors of Raffaele Rasoini

This figure shows the co-authorship network connecting the top 25 collaborators of Raffaele Rasoini. A scholar is included among the top collaborators of Raffaele Rasoini 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 Raffaele Rasoini. Raffaele Rasoini is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

1.

Rasoini, Raffaele, et al.. (2020). Nuove acquisizioni sulla gravità del danno cardiaco acuto in corso di COVID-19. Giornale italiano di cardiologia. 21(5). 328–331. 3 indexed citations

2.

Rasoini, Raffaele, et al.. (2020). Il re nudo nella pandemia: sulla produzione e comunicazione del sapere scientifico ai tempi di SARS-CoV-2. Recenti Progressi in Medicina. 111(7). 398–401.

3.

Cabitza, Federico, et al.. (2019). The elephant in the record: On the multiplicity of data recording work. Health Informatics Journal. 25(3). 475–490. 21 indexed citations

4.

Cabitza, Federico, et al.. (2017). Potenziali conseguenze inattese dell’uso di sistemi di intelligenza artificiale oracolari in medicina. Recenti Progressi in Medicina. 108(10). 397–401. 4 indexed citations

5.

Gensini, Gian Franco, et al.. (2017). Value of Telemonitoring and Telemedicine in Heart Failure Management. Cardiac failure review. 3(2). 1–1. 70 indexed citations

6.

Cabitza, Federico, Raffaele Rasoini, & Gian Franco Gensini. (2017). Unintended Consequences of Machine Learning in Medicine. JAMA. 318(6). 517–517. 604 indexed citations breakdown →

7.

Pace, Stefano Del, et al.. (2010). A 72-year-old man with intermittent fever, anemia and a history of coronary and peripheral artery disease. Internal and Emergency Medicine. 5(5). 415–420. 2 indexed citations

8.

Pace, Stefano Del, Maria Boddi, Raffaele Rasoini, et al.. (2010). Acute infection–inflammation and coronary stent thrombosis: an observational study. Internal and Emergency Medicine. 5(2). 121–126. 11 indexed citations

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.

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