Christian Salvatore

3.1k total citations · 1 hit paper
51 papers, 2.0k citations indexed

About

Christian Salvatore is a scholar working on Radiology, Nuclear Medicine and Imaging, Psychiatry and Mental health and Cognitive Neuroscience. According to data from OpenAlex, Christian Salvatore has authored 51 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Psychiatry and Mental health and 9 papers in Cognitive Neuroscience. Recurrent topics in Christian Salvatore's work include Radiomics and Machine Learning in Medical Imaging (15 papers), Dementia and Cognitive Impairment Research (9 papers) and Endometrial and Cervical Cancer Treatments (6 papers). Christian Salvatore is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (15 papers), Dementia and Cognitive Impairment Research (9 papers) and Endometrial and Cervical Cancer Treatments (6 papers). Christian Salvatore collaborates with scholars based in Italy, United States and United Kingdom. Christian Salvatore's co-authors include Isabella Castiglioni, Antonio Cerasa, Petronilla Battista, Matteo Interlenghi, Francesca Gallivanone, Maria Carla Gilardi, Aldo Quattrone, Francesco Sardanelli, Andrea Cozzi and Natascha Claudia D’Amico and has published in prestigious journals such as The Science of The Total Environment, Neuroscience & Biobehavioral Reviews and Journal of Autism and Developmental Disorders.

In The Last Decade

Christian Salvatore

45 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

AI applications to medical images: From machine learning to deep learning

2021 412 citations Isabella Castiglioni, Christian Salvatore et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Christian Salvatore Italy	22	634	438	348	340	302	51	2.0k
Sabina Tangaro Italy	27	855 1.3×	723 1.7×	365 1.0×	248 0.7×	284 0.9×	145	2.5k
Zhongxiang Ding China	23	1.2k 1.9×	431 1.0×	335 1.0×	147 0.4×	247 0.8×	126	2.2k
Roger Tam Canada	25	867 1.4×	297 0.7×	187 0.5×	249 0.7×	376 1.2×	115	2.2k
Francesca Gallivanone Italy	21	947 1.5×	237 0.5×	207 0.6×	240 0.7×	120 0.4×	51	1.9k
Vincent Noblet France	22	598 0.9×	144 0.3×	333 1.0×	262 0.8×	199 0.7×	94	1.6k
Yangming Ou United States	24	1.1k 1.7×	270 0.6×	463 1.3×	258 0.8×	293 1.0×	95	2.5k
Walter Hugo Lopez Pinaya United Kingdom	19	478 0.8×	326 0.7×	743 2.1×	256 0.8×	194 0.6×	43	1.5k
Ali R. Khan Canada	29	1.1k 1.7×	282 0.6×	581 1.7×	329 1.0×	186 0.6×	174	3.0k
Ricardo Guerrero United Kingdom	18	331 0.5×	372 0.8×	377 1.1×	386 1.1×	427 1.4×	40	1.7k
Nils D. Forkert Canada	33	917 1.4×	283 0.6×	450 1.3×	525 1.5×	401 1.3×	242	4.2k

Countries citing papers authored by Christian Salvatore

Since Specialization

Citations

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

Fields of papers citing papers by Christian Salvatore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Christian Salvatore

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

All Works

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20 of 20 papers shown

Lucchini, Alberto, Carolina Scala, Susan J. Sara, et al.. (2025). Impact of catheter size and endotracheal tube diameter on PEEP stability during closed suctioning in a simulated ARDS patient: a bench top study. Intensive and Critical Care Nursing. 92. 104233–104233.

Battista, Petronilla, et al.. (2025). Digital phenotyping of Parkinson’s disease via natural language processing. npj Parkinson s Disease. 11(1). 182–182. 3 indexed citations

Crimì, Filippo, Christian Salvatore, Matteo Interlenghi, et al.. (2024). A Machine Learning Model Based on MRI Radiomics to Predict Response to Chemoradiation Among Patients with Rectal Cancer. Life. 14(12). 1530–1530. 1 indexed citations

Gitto, Salvatore, Alessio Annovazzi, Matteo Interlenghi, et al.. (2024). X-rays radiomics-based machine learning classification of atypical cartilaginous tumour and high-grade chondrosarcoma of long bones. EBioMedicine. 101. 105018–105018. 9 indexed citations

Gargano, Marco, et al.. (2023). Giovanna Garzoni Miniaturist at the Savoy Court: Imaging and Materials Investigations to Discover the Painting Technique. Applied Sciences. 13(5). 2790–2790.

Aiello, Stefania, Christian Salvatore, Alessandro Venturi, et al.. (2023). A deep learning approach for automatic video coding of deictic gestures in children with autism. ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/). 1–6. 1 indexed citations

Interlenghi, Matteo, Giancarlo Sborgia, Alessandro Venturi, et al.. (2023). A Radiomic-Based Machine Learning System to Diagnose Age-Related Macular Degeneration from Ultra-Widefield Fundus Retinography. Diagnostics. 13(18). 2965–2965. 4 indexed citations

Albano, Domenico, Salvatore Gitto, Carmelo Messina, et al.. (2023). MRI-based artificial intelligence to predict infection following total hip arthroplasty failure. La radiologia medica. 128(3). 340–346. 12 indexed citations

Magni, Veronica, Matteo Interlenghi, Andrea Cozzi, et al.. (2022). Development and Validation of an AI-driven Mammographic Breast Density Classification Tool Based on Radiologist Consensus. Radiology Artificial Intelligence. 4(2). e210199–e210199. 26 indexed citations

10.

Interlenghi, Matteo, Christian Salvatore, Veronica Magni, et al.. (2022). A Machine Learning Ensemble Based on Radiomics to Predict BI-RADS Category and Reduce the Biopsy Rate of Ultrasound-Detected Suspicious Breast Masses. Diagnostics. 12(1). 187–187. 11 indexed citations

11.

Alì, Marco, Natascha Claudia D’Amico, Matteo Interlenghi, et al.. (2021). A Decision Support System Based on BI-RADS and Radiomic Classifiers to Reduce False Positive Breast Calcifications at Digital Breast Tomosynthesis: A Preliminary Study. Applied Sciences. 11(6). 2503–2503. 6 indexed citations

12.

Salvatore, Christian, Matteo Interlenghi, Caterina Beatrice Monti, et al.. (2021). Artificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia. Diagnostics. 11(3). 530–530. 14 indexed citations

13.

Chiappa, Valentina, Matteo Interlenghi, Christian Salvatore, et al.. (2021). Using rADioMIcs and machine learning with ultrasonography for the differential diagnosis of myometRiAL tumors (the ADMIRAL pilot study). Radiomics and differential diagnosis of myometrial tumors. Gynecologic Oncology. 161(3). 838–844. 32 indexed citations

14.

Chiappa, Valentina, Giorgio Bogani, Matteo Interlenghi, et al.. (2020). The Adoption of Radiomics and machine learning improves the diagnostic processes of women with Ovarian MAsses (the AROMA pilot study). Journal of Ultrasound. 24(4). 429–437. 43 indexed citations

15.

Gargano, Marco, Anna Gallì, Letizia Bonizzoni, et al.. (2018). The Giotto's workshop in the XXI century: looking inside the “God the Father with Angels” gable. Journal of Cultural Heritage. 36. 255–263. 18 indexed citations

16.

Crippa, Alessandro, Christian Salvatore, Erika Molteni, et al.. (2017). The Utility of a Computerized Algorithm Based on a Multi-Domain Profile of Measures for the Diagnosis of Attention Deficit/Hyperactivity Disorder. Frontiers in Psychiatry. 8. 189–189. 22 indexed citations

17.

Cerasa, Antonio, Isabella Castiglioni, Christian Salvatore, et al.. (2015). Biomarkers of Eating Disorders Using Support Vector Machine Analysis of Structural Neuroimaging Data: Preliminary Results. Behavioural Neurology. 2015. 1–10. 15 indexed citations

18.

Canini, Matteo, Petronilla Battista, Pasquale Anthony Della Rosa, et al.. (2014). Computerized Neuropsychological Assessment in Aging: Testing Efficacy and Clinical Ecology of Different Interfaces. Computational and Mathematical Methods in Medicine. 2014. 1–13. 35 indexed citations

19.

Chiriatti, Annalisa, Anita Mangia, Stefania Tommasi, et al.. (2007). P47 BRCA1, ER-alpha expression and molecular BRCA1 alterations in familial and sporadic breast cancer. European Journal of Cancer Supplements. 5(8). 21–21. 1 indexed citations

20.

Salvatore, Christian, et al.. (1997). La febbre alta nel lattante e nel bambino sotto i tre anni. Medico e Bambino. 16(3). 171.

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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