Daniela Schenone

500 citations
13 papers · 319 · h-index 7

Impact in

Papers in

Daniela Schenone

11 papers receiving 314 citations

Peers

Daniela Schenone
Comparison fields: 5 of 77
  • Health Informatics 15
  • Radiology, Nuclear Medicine and Imaging 192
  • Artificial Intelligence 97
  • Computer Vision and Pattern Recognition 40
  • Hematology 21
Replace Daniel Smutek with:
Daniel Smutek Czechia
Guilherme Moura Cunha United States
Nick Weiss Germany
Jim Diamond United Kingdom
Shulong Li China
Gil Shamai Israel
Wei-Chih Shen Taiwan
Turid Torheim United Kingdom
Deepak R. Chittajallu United States
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Daniela Schenone relative to Daniel Smutek Czechia Daniel Smutek's profile →
Citations per field
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Citations per year

Countries citing papers authored by Daniela Schenone

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Schenone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniela Schenone, 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 Daniela Schenone Line = papers co-authored together Daniela Schenone links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2019203
2 201851
3 201722
4 202112
5 20219
6 20227
7 20207
8 20203
9 20183
10 20211
11
[Treatment of Taenia saginata infections in adults with a single oral dose of praziquantel (author's transl)].
19801
12 20230
13 20200

About Daniela Schenone

Daniela Schenone is a scholar working on Radiology, Nuclear Medicine and Imaging, Hematology, Computer Vision and Pattern Recognition, Oncology and Surgery, having authored 13 papers that have together received 319 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), Multiple Myeloma Research and Treatments (4 papers), Image and Signal Denoising Methods (2 papers), Management of metastatic bone disease (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Colorectal Cancer Treatments and Studies (1 paper), Lymphoma Diagnosis and Treatment (1 paper) and Bone health and treatments (1 paper). The work is most often cited by research in Health Informatics (15 citations), Radiology, Nuclear Medicine and Imaging (192 citations), Artificial Intelligence (97 citations), Computer Vision and Pattern Recognition (40 citations) and Hematology (21 citations). Daniela Schenone has collaborated with scholars based in Italy, Australia and Spain. Frequent co-authors include Michele Piana, Alberto Tagliafico, Nehmat Houssami, Anna Maria Massone, Lucia Romani, Costanza Conti, Alida Dominietto, Cristina Campi, Liliana Belgioia and Federica Rossi. Their work appears in journals such as Cancer Imaging, Annals of Nuclear Medicine, The Breast, Applied Mathematics and Computation and Pattern Recognition.

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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