Giovanni Angelotti

458 total citations
17 papers, 174 citations indexed

About

Giovanni Angelotti is a scholar working on Infectious Diseases, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Giovanni Angelotti has authored 17 papers receiving a total of 174 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Infectious Diseases, 5 papers in Artificial Intelligence and 4 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Giovanni Angelotti's work include COVID-19 Clinical Research Studies (5 papers), Machine Learning in Healthcare (4 papers) and COVID-19 diagnosis using AI (3 papers). Giovanni Angelotti is often cited by papers focused on COVID-19 Clinical Research Studies (5 papers), Machine Learning in Healthcare (4 papers) and COVID-19 diagnosis using AI (3 papers). Giovanni Angelotti collaborates with scholars based in Italy, United States and United Kingdom. Giovanni Angelotti's co-authors include Victor Savevski, Letterio S. Politi, Pierandrea Morandini, Ezio Lanza, Luca Balzarini, Riccardo Muglia, Maurizio Cecconi, Massimiliano Greco, Riccardo Levi and Alessio Aghemo and has published in prestigious journals such as European Radiology, Applied Sciences and Viruses.

In The Last Decade

Giovanni Angelotti

17 papers receiving 174 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Giovanni Angelotti Italy	8	91	58	43	36	28	17	174
Zeno Falaschi Italy	9	158 1.7×	67 1.2×	27 0.6×	53 1.5×	42 1.5×	18	260
Pierandrea Morandini Italy	5	76 0.8×	44 0.8×	26 0.6×	32 0.9×	16 0.6×	9	121
Nakeya Dewaswala United States	9	62 0.7×	67 1.2×	26 0.6×	44 1.2×	21 0.8×	39	228
Junaid Mushtaq Italy	7	95 1.0×	29 0.5×	42 1.0×	91 2.5×	24 0.9×	9	220
Silvia Luvarà Italy	5	173 1.9×	85 1.5×	24 0.6×	58 1.6×	32 1.1×	6	268
Pietro Danna Italy	5	80 0.9×	42 0.7×	17 0.4×	23 0.6×	25 0.9×	7	126
Luca Mingardi United States	4	58 0.6×	56 1.0×	25 0.6×	16 0.4×	47 1.7×	5	183
Joseph Bae United States	7	70 0.8×	29 0.5×	11 0.3×	38 1.1×	43 1.5×	13	190
Xun Ding China	7	121 1.3×	123 2.1×	50 1.2×	61 1.7×	21 0.8×	18	284
Silvia Lucarini Italy	5	173 1.9×	80 1.4×	23 0.5×	67 1.9×	32 1.1×	10	276

Countries citing papers authored by Giovanni Angelotti

Since Specialization

Citations

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

Fields of papers citing papers by Giovanni Angelotti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giovanni Angelotti

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

All Works

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17 of 17 papers shown

Pensato, Umberto, et al.. (2024). Development of a Natural Language Processing (NLP) model to automatically extract clinical data from electronic health records: results from an Italian comprehensive stroke center. International Journal of Medical Informatics. 192. 105626–105626. 3 indexed citations

Angelotti, Giovanni, et al.. (2024). A Closer Look at AUROC and AUPRC under Class Imbalance. 44102–44163. 2 indexed citations

Greco, Massimiliano, Giovanni Angelotti, Romina Aceto, et al.. (2023). REVersal of nEuromusculAr bLocking Agents in Patients Undergoing General Anaesthesia (REVEAL Study). Journal of Clinical Medicine. 12(2). 563–563. 1 indexed citations

Colapietro, Francesca, Giovanni Angelotti, Chiara Masetti, et al.. (2023). Ursodeoxycholic Acid Does Not Improve COVID-19 Outcome in Hospitalized Patients. Viruses. 15(8). 1738–1738. 12 indexed citations

Levi, Riccardo, Giovanni Savini, Marco Riva, et al.. (2023). CT-based radiomics can identify physiological modifications of bone structure related to subjects’ age and sex. La radiologia medica. 128(6). 744–754. 12 indexed citations

Greco, Massimiliano, et al.. (2023). Implementing Artificial Intelligence. Critical Care Clinics. 39(4). 783–793. 6 indexed citations

Greco, Massimiliano, Giovanni Angelotti, Alberto Zanella, et al.. (2022). Outcome prediction during an ICU surge using a purely data-driven approach: A supervised machine learning case-study in critically ill patients from COVID-19 Lombardy outbreak. International Journal of Medical Informatics. 164. 104807–104807. 8 indexed citations

Angelotti, Giovanni, Massimiliano Greco, Giorgio Guzzetta, et al.. (2022). Early prediction of SARS-CoV-2 reproductive number from environmental, atmospheric and mobility data: A supervised machine learning approach. International Journal of Medical Informatics. 162. 104755–104755. 5 indexed citations

Laino, Maria Elena, Elena Generali, Giovanni Angelotti, et al.. (2022). An Individualized Algorithm to Predict Mortality in COVID-19 Pneumonia: a Machine Learning Based Study. Archives of Medical Science. 18(3). 587–595. 8 indexed citations

10.

Morandini, Pierandrea, Maria Elena Laino, Giovanni Paoletti, et al.. (2022). Artificial intelligence processing electronic health records to identify commonalities and comorbidities cluster at Immuno Center Humanitas. Clinical and Translational Allergy. 12(6). e12144–e12144. 4 indexed citations

11.

Levi, Riccardo, Chiara Pozzi, Giovanni Angelotti, et al.. (2021). The antibody response to SARS-CoV-2 infection persists over at least 8 months in symptomatic patients. Communications Medicine. 1(1). 32–32. 10 indexed citations

12.

Angelotti, Giovanni, Massimiliano Greco, Victor Savevski, et al.. (2021). The effect of COVID-19 epidemic on vital signs in hospitalized patients: a pre-post heat-map study from a large teaching hospital. Journal of Clinical Monitoring and Computing. 36(3). 829–837. 8 indexed citations

13.

Voza, Antonio, Sabino Luzzi, Alice Giotta Lucifero, et al.. (2021). Clinical Outcomes in the Second versus First Pandemic Wave in Italy: Impact of Hospital Changes and Reorganization. Applied Sciences. 11(19). 9342–9342. 2 indexed citations

14.

Angelotti, Giovanni, et al.. (2020). ICU management based on big data. Current Opinion in Anaesthesiology. 33(2). 162–169. 7 indexed citations

15.

Lanza, Ezio, Riccardo Muglia, Giovanni Angelotti, et al.. (2020). Quantitative chest CT analysis in COVID-19 to predict the need for oxygenation support and intubation. European Radiology. 30(12). 6770–6778. 84 indexed citations

16.

Angelotti, Giovanni, et al.. (2018). The Role of Baroreflex Sensitivity in Acute Hypotensive Episodes Prediction in the Intensive Care Unit. PubMed. 101. 2784–2787. 1 indexed citations

17.

Angelotti, Giovanni, et al.. (1988). [Postoperative analgesia with peridural morphine. Comparative study in thoracic and abdominal surgery].. PubMed. 54(12). 521–4. 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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