Nicola Altini

564 total citations
26 papers, 343 citations indexed

About

Nicola Altini is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nicola Altini has authored 26 papers receiving a total of 343 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Artificial Intelligence and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nicola Altini's work include Radiomics and Machine Learning in Medical Imaging (11 papers), AI in cancer detection (11 papers) and Medical Image Segmentation Techniques (4 papers). Nicola Altini is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (11 papers), AI in cancer detection (11 papers) and Medical Image Segmentation Techniques (4 papers). Nicola Altini collaborates with scholars based in Italy, Germany and Spain. Nicola Altini's co-authors include Vitoantonio Bevilacqua, Antonio Brunetti, Giacomo Donato Cascarano, Domenico Buongiorno, Andrea Guerriero, Francescomaria Marino, Francesco Pesce, Loreto Gesualdo, Michele Rossini and Francesco Alfredo Zito and has published in prestigious journals such as Sensors, Neurocomputing and Applied Sciences.

In The Last Decade

Nicola Altini

23 papers receiving 337 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nicola Altini Italy 12 172 153 102 50 50 26 343
Tao Tan China 12 161 0.9× 170 1.1× 87 0.9× 62 1.2× 69 1.4× 55 403
Vivek Natarajan United States 5 204 1.2× 196 1.3× 89 0.9× 34 0.7× 32 0.6× 7 367
Tomas Sakinis Norway 7 103 0.6× 265 1.7× 68 0.7× 52 1.0× 92 1.8× 10 499
Shujun Liang China 9 182 1.1× 309 2.0× 105 1.0× 44 0.9× 72 1.4× 20 467
Zeshan Hussain United States 5 114 0.7× 133 0.9× 69 0.7× 25 0.5× 61 1.2× 5 298
Helena R. Torres Portugal 10 69 0.4× 106 0.7× 140 1.4× 47 0.9× 83 1.7× 47 302
Cai Chang China 14 315 1.8× 330 2.2× 117 1.1× 53 1.1× 68 1.4× 39 548
Ryoungwoo Jang South Korea 7 124 0.7× 214 1.4× 51 0.5× 49 1.0× 113 2.3× 8 398
Yuting Guo China 9 107 0.6× 144 0.9× 32 0.3× 40 0.8× 47 0.9× 25 297

Countries citing papers authored by Nicola Altini

Since Specialization
Citations

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

Fields of papers citing papers by Nicola Altini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicola Altini

This figure shows the co-authorship network connecting the top 25 collaborators of Nicola Altini. A scholar is included among the top collaborators of Nicola Altini 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 Nicola Altini. Nicola Altini 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
1.
Zaccaria, Gian Maria, et al.. (2025). Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma. International Journal of Medical Informatics. 199. 105883–105883.
2.
Altini, Nicola, Rosalba D’Alessandro, Angela Dalia Ricci, et al.. (2025). Pharmacometric and Digital Twin modeling for adaptive scheduling of combination therapy in advanced gastric cancer. Computer Methods and Programs in Biomedicine. 270. 108919–108919. 2 indexed citations
3.
Zaccaria, Gian Maria, et al.. (2025). A multimodal framework for assessing the link between pathomics, transcriptomics, and pancreatic cancer mutations. Computerized Medical Imaging and Graphics. 123. 102526–102526. 1 indexed citations
4.
Altini, Nicola, et al.. (2025). A Comparison Between Unimodal and Multimodal Segmentation Models for Deep Brain Structures from T1- and T2-Weighted MRI. Machine Learning and Knowledge Extraction. 7(3). 84–84. 1 indexed citations
5.
Altini, Nicola, Vitoantonio Bevilacqua, Michele Rossini, et al.. (2025). Permutation-Invariant Cascaded Attentional Set Operator for Computational Nephropathology. Kidney360. 6(3). 441–450.
6.
7.
Zaccaria, Gian Maria, et al.. (2024). A time-dependent explainable radiomic analysis from the multi-omic cohort of CPTAC-Pancreatic Ductal Adenocarcinoma. Computer Methods and Programs in Biomedicine. 257. 108408–108408. 4 indexed citations
8.
9.
Pedraza, Aníbal, et al.. (2024). GNCnn: A QuPath extension for glomerulosclerosis and glomerulonephritis characterization based on deep learning. Computational and Structural Biotechnology Journal. 27. 35–47.
10.
Altini, Nicola, Francescomaria Marino, Simona De Summa, et al.. (2023). Tumor Cellularity Assessment of Breast Histopathological Slides via Instance Segmentation and Pathomic Features Explainability. Bioengineering. 10(4). 396–396. 15 indexed citations
11.
Zaccaria, Gian Maria, Nicola Altini, Maria Carmela Vegliante, et al.. (2023). SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data. Computer Methods and Programs in Biomedicine. 244. 107966–107966. 7 indexed citations
12.
Altini, Nicola, Francesco Alfredo Zito, Stefania Tommasi, et al.. (2023). The role of unpaired image-to-image translation for stain color normalization in colorectal cancer histology classification. Computer Methods and Programs in Biomedicine. 234. 107511–107511. 20 indexed citations
13.
Zaccaria, Gian Maria, Maria Carmela Vegliante, Giacomo Volpe, et al.. (2023). A Decision-tree Approach to Stratify DLBCL Risk Based on Stromal and Immune Microenvironment Determinants. HemaSphere. 7(4). e862–e862. 5 indexed citations
14.
Gravina, Matteo, et al.. (2023). An Explainable Radiogenomic Framework to Predict Mutational Status of KRAS and EGFR in Lung Adenocarcinoma Patients. Bioengineering. 10(7). 747–747. 11 indexed citations
15.
Altini, Nicola, Antonio Brunetti, Concetta Saponaro, et al.. (2022). NDG-CAM: Nuclei Detection in Histopathology Images with Semantic Segmentation Networks and Grad-CAM. Bioengineering. 9(9). 475–475. 19 indexed citations
16.
Brunetti, Antonio, et al.. (2022). A Machine Learning and Radiomics Approach in Lung Cancer for Predicting Histological Subtype. Applied Sciences. 12(12). 5829–5829. 11 indexed citations
17.
Altini, Nicola, Antonio Brunetti, Stefano Mazzoleni, et al.. (2021). Predictive Machine Learning Models and Survival Analysis for COVID-19 Prognosis Based on Hematochemical Parameters. Sensors. 21(24). 8503–8503. 10 indexed citations
18.
Altini, Nicola, et al.. (2021). Segmentation and Identification of Vertebrae in CT Scans Using CNN, k-Means Clustering and k-NN. Informatics. 8(2). 40–40. 32 indexed citations
19.
20.
Altini, Nicola, Giacomo Donato Cascarano, Antonio Brunetti, et al.. (2020). Semantic Segmentation Framework for Glomeruli Detection and Classification in Kidney Histological Sections. Electronics. 9(3). 503–503. 51 indexed citations

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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