Francesco Molà

38 papers and 366 indexed citations i.

About

Francesco Molà is a scholar working on Artificial Intelligence, Pharmacology and Sociology and Political Science. According to data from OpenAlex, Francesco Molà has authored 38 papers receiving a total of 366 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 7 papers in Pharmacology and 6 papers in Sociology and Political Science. Recurrent topics in Francesco Molà’s work include Data Mining Algorithms and Applications (6 papers), Musculoskeletal pain and rehabilitation (4 papers) and Sentiment Analysis and Opinion Mining (4 papers). Francesco Molà is often cited by papers focused on Data Mining Algorithms and Applications (6 papers), Musculoskeletal pain and rehabilitation (4 papers) and Sentiment Analysis and Opinion Mining (4 papers). Francesco Molà collaborates with scholars based in Italy, Canada and Czechia. Francesco Molà's co-authors include Roberta Siciliano, Luca Frigau, Claudio Conversano, Marco Monticone, Gianfranco Fancello, Paolo Fadda, Gianluigi Bacchetta, Giuseppe Marongiu, Alessandra Carucci and Giovanna Cappai and has published in prestigious journals such as BMC Cancer, European Spine Journal and Progress in Neuro-Psychopharmacology and Biological Psychiatry.

In The Last Decade

Co-authorship network of co-authors of Francesco Molà i

Fields of papers citing papers by Francesco Molà

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Francesco Molà

Since Specialization
Citations

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

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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