Annalisa Nardone

495 total citations
24 papers, 271 citations indexed

About

Annalisa Nardone is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Annalisa Nardone has authored 24 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Pulmonary and Respiratory Medicine and 7 papers in Artificial Intelligence. Recurrent topics in Annalisa Nardone's work include Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers) and Breast Cancer Treatment Studies (6 papers). Annalisa Nardone is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (9 papers), AI in cancer detection (7 papers) and Breast Cancer Treatment Studies (6 papers). Annalisa Nardone collaborates with scholars based in Italy, China and Türkiye. Annalisa Nardone's co-authors include Annarita Fanizzi, Raffaella Massafra, Samantha Bove, Maria Colomba Comes, Pasquale Tamborra, Daniele La Forgia, Vittorio Didonna, Vito Lorusso, Agnese Latorre and Eugenio Martinelli and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Annalisa Nardone

22 papers receiving 266 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Annalisa Nardone Italy 10 133 118 78 78 40 24 271
Christina Glasner Germany 3 153 1.2× 129 1.1× 62 0.8× 93 1.2× 53 1.3× 4 279
Vidya Sankar Viswanathan United States 10 179 1.3× 91 0.8× 93 1.2× 101 1.3× 32 0.8× 39 307
Kyunghyun Paeng South Korea 9 136 1.0× 104 0.9× 58 0.7× 92 1.2× 48 1.2× 29 237
Toshiyuki Ishiba Japan 9 163 1.2× 123 1.0× 68 0.9× 68 0.9× 75 1.9× 35 331
Charles Maussion France 4 178 1.3× 190 1.6× 74 0.9× 67 0.9× 57 1.4× 12 338
Jing Hang China 10 177 1.3× 101 0.9× 55 0.7× 39 0.5× 62 1.6× 21 323
Nicolas Brieu Germany 11 120 0.9× 93 0.8× 45 0.6× 121 1.6× 39 1.0× 27 273
Paula Toro United States 8 125 0.9× 92 0.8× 56 0.7× 58 0.7× 37 0.9× 27 239
Aurélie Fernandez Germany 5 181 1.4× 151 1.3× 85 1.1× 119 1.5× 64 1.6× 8 353
Rebecca Batiste United States 5 132 1.0× 114 1.0× 53 0.7× 49 0.6× 43 1.1× 7 265

Countries citing papers authored by Annalisa Nardone

Since Specialization
Citations

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

Fields of papers citing papers by Annalisa Nardone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Annalisa Nardone

This figure shows the co-authorship network connecting the top 25 collaborators of Annalisa Nardone. A scholar is included among the top collaborators of Annalisa Nardone 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 Annalisa Nardone. Annalisa Nardone 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.
Comes, Maria Colomba, Annarita Fanizzi, Samantha Bove, et al.. (2024). Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy. Computers in Biology and Medicine. 172. 108132–108132. 8 indexed citations
2.
Longo, Vito, Annamaria Catino, Michele Montrone, et al.. (2024). Treatment of Thoracic SMARCA4-Deficient Undifferentiated Tumors: Where We Are and Where We Will Go. International Journal of Molecular Sciences. 25(6). 3237–3237. 10 indexed citations
3.
Fanizzi, Annarita, Samantha Bove, Maria Colomba Comes, et al.. (2024). Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form. PLoS ONE. 19(11). e0312036–e0312036.
4.
5.
Montrone, Michele, Gerardo Rosati, Vito Longo, et al.. (2023). Immunotherapy in Elderly Patients Affected by Non-Small Cell Lung Cancer: A Narrative Review. Journal of Clinical Medicine. 12(5). 1833–1833. 8 indexed citations
6.
Bove, Samantha, Annarita Fanizzi, Maria Colomba Comes, et al.. (2023). A CT-based transfer learning approach to predict NSCLC recurrence: The added-value of peritumoral region. PLoS ONE. 18(5). e0285188–e0285188. 14 indexed citations
7.
Fanizzi, Annarita, Samantha Bove, Maria Colomba Comes, et al.. (2023). A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients. Healthcare. 11(7). 1042–1042. 5 indexed citations
8.
Fanizzi, Annarita, Maria Colomba Comes, Samantha Bove, et al.. (2023). Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence. Scientific Reports. 13(1). 20605–20605. 14 indexed citations
9.
Massafra, Raffaella, Maria Colomba Comes, Samantha Bove, et al.. (2022). A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification. PLoS ONE. 17(9). e0274691–e0274691. 11 indexed citations
10.
Massafra, Raffaella, Samantha Bove, Daniele La Forgia, et al.. (2022). An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients’ Age: A Retrospective Cohort Study. Cancers. 14(9). 2215–2215. 6 indexed citations
11.
Massafra, Raffaella, Agnese Latorre, Annarita Fanizzi, et al.. (2021). A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results. Frontiers in Oncology. 11. 576007–576007. 28 indexed citations
12.
Comes, Maria Colomba, Annarita Fanizzi, Samantha Bove, et al.. (2021). Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs. Scientific Reports. 11(1). 14123–14123. 54 indexed citations
13.
Fanizzi, Annarita, Vito Lorusso, Samantha Bove, et al.. (2021). Sentinel Lymph Node Metastasis on Clinically Negative Patients: Preliminary Results of a Machine Learning Model Based on Histopathological Features. Applied Sciences. 11(21). 10372–10372. 6 indexed citations
14.
15.
Guida, Michele, Nicola Bartolomeo, Ivana De Risi, et al.. (2019). The Management of Oligoprogression in the Landscape of New Therapies for Metastatic Melanoma. Cancers. 11(10). 1559–1559. 19 indexed citations
16.
17.
Rella, Leonarda, Michele Telegrafo, Annalisa Nardone, et al.. (2015). MRI evaluation of post-mastectomy irradiated breast implants: prevalence and analysis of complications. Clinical Radiology. 70(9). 948–953. 10 indexed citations
18.
Salvati, Maurizio, Emanuela Caroli, E Orlando, et al.. (2004). Solitary Brain Metastases from Uterus Carcinoma: Report of Three Cases. Journal of Neuro-Oncology. 66(1-2). 175–178. 14 indexed citations
19.
Nardone, Annalisa, et al.. (2000). [Video laparoscopic cholecystectomy in a female patient with cholelithiasis in Steinert's myotonic dystrophy].. PubMed. 71(1). 139–43. 2 indexed citations
20.
Negri, Pedro, et al.. (1998). [Acute cholecystitis and gallbladder neoplasms: the experience of 2215 cases].. PubMed. 19(10). 391–4. 1 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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