M. Signorini

472 citations
22 papers · 325 indexed · h-index 10
Topics
Radiomics and Machine Learning in Medical Imaging (3 papers)Wound Healing and Treatments (3 papers)Burn Injury Management and Outcomes (3 papers)
Partner nations
ItalyUnited StatesEgypt

In The Last Decade

M. Signorini

22 papers receiving 312 citations

Peers

M. Signorini
Comparison fields: 5 of 66
  • Dermatology 104
  • Surgery 102
  • Neurology 73
  • Rehabilitation 73
  • Epidemiology 65
Replace Ann F. Haas with:
Ann F. Haas United States
Nazan Sivrioğlu Türkiye
Mauro Tarallo Italy
Sheri L. DeMartelaere United States
J Meine United States
Shiow-Shuh Chuang Taiwan
Bradley S. Bloom United States
Chin-Chiang Yang Taiwan
Douglas D. Leventhal United States
Luca Negosanti Italy
M. Signorini relative to Ann F. Haas United States Ann F. Haas's profile →
Citations per field
00.5×
Ann F. Haas · 1×
Citations per year

Countries citing papers authored by M. Signorini

Since Specialization
Citations

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

Fields of papers citing papers by M. Signorini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Signorini

This figure shows the co-authorship network connecting the top 25 collaborators of M. Signorini. A scholar is included among the top collaborators of M. Signorini 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 M. Signorini. M. Signorini 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 5
2 3
3 91
4 6
5 19
6 20
7 30
8
[Optic pathway gliomas in patients with neurofibromatosis type 1: clinical-neuroradiological integrated approach].
2
9 1
10 4
11 3
12 1
13
[Ear prostheses in burns of the external ear. Technical notes].
4
14 21
15 6
16 2
17 43
18 21
19 21
20 1

About M. Signorini

M. Signorini is a scholar working on Dermatology, Rehabilitation and Neurology, having authored 22 papers that have together received 325 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), Wound Healing and Treatments (3 papers) and Burn Injury Management and Outcomes (3 papers). The work is most often cited by research in Dermatology (104 citations), Rehabilitation (73 citations) and Neurology (73 citations). M. Signorini has collaborated with scholars based in Italy, United States and Egypt. Frequent co-authors include Maurício de Maio, Arthur Swift, Steven Fagien, Lorenzo Donati, Franz Wilhelm Baruffaldi Preis, G. Magliacani, Marco Klinger, Simone Perandini, Enrico Magliano and Massimiliano Motton. Their work appears in journals such as Plastic & Reconstructive Surgery, Physical Therapy and European Radiology.

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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