Corrado Lanera

872 citations
55 papers · 534 · h-index 14

Impact in

Papers in

Corrado Lanera

50 papers receiving 520 citations

Peers

Corrado Lanera
Comparison fields: 5 of 125
  • Health Informatics 43
  • Health Information Management 40
  • Modeling and Simulation 32
  • Health, Toxicology and Mutagenesis 68
  • Cardiology and Cardiovascular Medicine 98
Replace Bilal A. Mateen with:
Bilal A. Mateen United Kingdom
Joshua Kaminsky United States
Santiago Romero‐Brufau United States
Yuji Nishizaki Japan
Arya Aminorroaya United States
Ramkiran Gouripeddi United States
Katherine McAllister United Kingdom
Flory L. Nkoy United States
Gina Barnes United States
José Benuzillo United States
Corrado Lanera relative to Bilal A. Mateen United Kingdom Bilal A. Mateen's profile →
Citations per field
00.5×
Bilal A. Mateen · 1×
Citations per year

Countries citing papers authored by Corrado Lanera

Since Specialization
Citations

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

Fields of papers citing papers by Corrado Lanera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Corrado Lanera, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Corrado Lanera Line = papers co-authored together Corrado Lanera links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201755
2 201941
3 202132
4 201729
5 202028
6 202024
7 201922
8 201720
9 201917
10
Bayesian Machine Learning Techniques for revealing complex interactions among genetic and clinical factors in association with extra-intestinal Manifestations in IBD patients.
201616
11 202115
12 201915
13 201914
14 202014
15 202212
16 201812
17 202112
18 202111
19 201810
20 202210

About Corrado Lanera

Corrado Lanera is a scholar working on Epidemiology, Cardiology and Cardiovascular Medicine, General Health Professions, Artificial Intelligence and Surgery, having authored 55 papers that have together received 534 indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (7 papers), COVID-19 epidemiological studies (6 papers), Cardiac pacing and defibrillation studies (5 papers), Cardiac Arrhythmias and Treatments (4 papers), Machine Learning in Healthcare (4 papers), Cardiac Structural Anomalies and Repair (3 papers), Cardiac electrophysiology and arrhythmias (3 papers) and Health Systems, Economic Evaluations, Quality of Life (3 papers). The work is most often cited by research in Health Informatics (43 citations), Health Information Management (40 citations), Modeling and Simulation (32 citations), Health, Toxicology and Mutagenesis (68 citations) and Cardiology and Cardiovascular Medicine (98 citations). Corrado Lanera has collaborated with scholars based in Italy, United States and India. Frequent co-authors include Darío Gregori, Paola Berchialla, Giulia Lorenzoni, Ileana Baldi, Danila Azzolina, Honoria Ocagli, Daniele Bottigliengo, Sabino Iliceto, Clara Minto and Gino Gerosa. Their work appears in journals such as International Journal of Environmental Research and Public Health, Scientific Reports, International Journal of Cardiology, Foods and Journal of Personalized Medicine.

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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