Francesco Molà

893 citations
44 papers · 442 indexed · h-index 12
Topics
Data Mining Algorithms and Applications (6 papers)Sentiment Analysis and Opinion Mining (4 papers)Musculoskeletal pain and rehabilitation (4 papers)
Partner nations
ItalyCanadaPoland

In The Last Decade

Francesco Molà

41 papers receiving 425 citations

Peers

Francesco Molà
Comparison fields: 5 of 130
  • Artificial Intelligence 72
  • Surgery 63
  • Pharmacology 45
  • Ocean Engineering 42
  • Industrial and Manufacturing Engineering 40
Replace Ahmet Fahri Özok with:
Ahmet Fahri Özok Türkiye
Kiran Pandey India
Leorey Marquez Australia
Ran Ji United States
Ying Lv China
Sadeque Hamdan United Arab Emirates
Navneet Bhushan India
B. Wang China
Liu Jing China
Francesco Molà relative to Ahmet Fahri Özok Türkiye Ahmet Fahri Özok's profile →
Citations per field
00.5×20×40×63×
Ahmet Fahri Özok · 1×
Citations per year

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).

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.

Co-authorship network of co-authors of Francesco Molà

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 1
3 7
4 3
5 7
6 8
7 1
8 32
9 27
10 16
11 9
12 4
13 4
14 11
15 17
16 3
17
Classification of Images Background Subtraction in Image Segmentation
0
18 46
19 1
20
A Statistical Approach to Neural Networks
1

About Francesco Molà

Francesco Molà is a scholar working on Marketing, Pharmacology and Biological Psychiatry, having authored 44 papers that have together received 442 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (6 papers), Sentiment Analysis and Opinion Mining (4 papers) and Musculoskeletal pain and rehabilitation (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (40 citations), Health Informatics (4 citations) and Statistics and Probability (24 citations). Francesco Molà has collaborated with scholars based in Italy, Canada and Poland. Frequent co-authors include Roberta Siciliano, Luca Frigau, Claudio Conversano, Gianfranco Fancello, Paolo Fadda, Marco Monticone, Gianluigi Bacchetta, Antonio Capone, Giuseppe Marongiu and A Cao. Their work appears in journals such as BMC Cancer, European Spine Journal and Progress in Neuro-Psychopharmacology and Biological Psychiatry.

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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