Gian Marco Conte

1.3k total citations
35 papers, 691 citations indexed

About

Gian Marco Conte is a scholar working on Radiology, Nuclear Medicine and Imaging, Genetics and Neurology. According to data from OpenAlex, Gian Marco Conte has authored 35 papers receiving a total of 691 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Genetics and 5 papers in Neurology. Recurrent topics in Gian Marco Conte's work include Radiomics and Machine Learning in Medical Imaging (11 papers), MRI in cancer diagnosis (6 papers) and Glioma Diagnosis and Treatment (6 papers). Gian Marco Conte is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (11 papers), MRI in cancer diagnosis (6 papers) and Glioma Diagnosis and Treatment (6 papers). Gian Marco Conte collaborates with scholars based in United States, Italy and Chile. Gian Marco Conte's co-authors include Bradley J. Erickson, Pouria Rouzrokh, Nicoletta Anzalone, Kenneth A. Philbrick, Mana Moassefi, Antonella Castellano, Shahriar Faghani, Andrea Falini, Bardia Khosravi and Marcello Cadioli and has published in prestigious journals such as SHILAP Revista de lepidopterología, Neurology and Radiology.

In The Last Decade

Gian Marco Conte

33 papers receiving 684 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gian Marco Conte United States	15	413	198	93	92	90	35	691
Gianluca Brugnara Germany	11	424 1.0×	209 1.1×	68 0.7×	74 0.8×	92 1.0×	32	778
Luke Macyszyn United States	16	410 1.0×	274 1.4×	193 2.1×	94 1.0×	59 0.7×	44	975
Frank Thiele Germany	14	288 0.7×	130 0.7×	63 0.7×	63 0.7×	79 0.9×	27	586
Raphael Meier Switzerland	16	455 1.1×	168 0.8×	106 1.1×	254 2.8×	219 2.4×	36	1.0k
Hiroyuki Uetani Japan	18	666 1.6×	217 1.1×	198 2.1×	41 0.4×	44 0.5×	89	1.1k
Shahriar Faghani United States	16	297 0.7×	41 0.2×	130 1.4×	141 1.5×	41 0.5×	57	680
Jonathan D Suever United States	18	406 1.0×	54 0.3×	140 1.5×	95 1.0×	22 0.2×	42	1.4k
Mark Attiah United States	16	212 0.5×	145 0.7×	129 1.4×	47 0.5×	29 0.3×	40	830
Kelsey L. Pomykala Germany	13	317 0.8×	175 0.9×	43 0.5×	65 0.7×	29 0.3×	42	772
Ulf Neuberger Germany	10	492 1.2×	285 1.4×	65 0.7×	67 0.7×	79 0.9×	15	761

Countries citing papers authored by Gian Marco Conte

Since Specialization

Citations

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

Fields of papers citing papers by Gian Marco Conte

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gian Marco Conte. 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 Gian Marco Conte. The network helps show where Gian Marco Conte may publish in the future.

Co-authorship network of co-authors of Gian Marco Conte

This figure shows the co-authorship network connecting the top 25 collaborators of Gian Marco Conte. A scholar is included among the top collaborators of Gian Marco Conte 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 Gian Marco Conte. Gian Marco Conte 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

Moassefi, Mana, Shahriar Faghani, Gian Marco Conte, et al.. (2024). Exploring the Impact of 3D Fast Spin Echo and Inversion Recovery Gradient Echo Sequences Magnetic Resonance Imaging Acquisition on Automated Brain Tumor Segmentation. SHILAP Revista de lepidopterología. 2(2). 231–240.

Conte, Gian Marco, et al.. (2024). Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis. 4. e56679–e56679.

Conte, Gian Marco, et al.. (2024). Accelerometer‐Measured Behavior Patterns in Incident Cerebrovascular Disease: Insights for Preventative Monitoring From the UK Biobank. Journal of the American Heart Association. 13(11). e032965–e032965. 2 indexed citations

Conte, Gian Marco, et al.. (2024). Generative Adversarial Networks for Brain MRI Synthesis: Impact of Training Set Size on Clinical Application. Journal of Imaging Informatics in Medicine. 37(3). 1228–1238. 1 indexed citations

Moassefi, Mana, Yashbir Singh, Gian Marco Conte, et al.. (2024). Checklist for Reproducibility of Deep Learning in Medical Imaging. Journal of Imaging Informatics in Medicine. 37(4). 1664–1673. 6 indexed citations

Conte, Gian Marco, Mana Moassefi, Shahriar Faghani, et al.. (2023). NIMG-57. PERFORMANCE OF DEEP LEARNING IN MGMT PROMOTER METHYLATION STATUS PREDICTION USING BRAIN MRI: RESULTS FROM A LARGE COHORT OF IDH-WILDTYPE GLIOMAS TESTED BY A SINGLE METHYLATION ASSAY. Neuro-Oncology. 25(Supplement_5). v199–v199. 1 indexed citations

Conte, Gian Marco, et al.. (2023). In Situ Physiologic and Behavioral Monitoring With Digital Sensors for Cerebrovascular Disease: A Scoping Review. SHILAP Revista de lepidopterología. 1(2). 139–160. 4 indexed citations

Faghani, Shahriar, Bardia Khosravi, Mana Moassefi, Gian Marco Conte, & Bradley J. Erickson. (2023). A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI. Journal of Digital Imaging. 36(3). 837–846. 25 indexed citations

Moassefi, Mana, Pouria Rouzrokh, Gian Marco Conte, et al.. (2023). Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review. Journal of Digital Imaging. 36(5). 2306–2312. 11 indexed citations

10.

Rouzrokh, Pouria, Bardia Khosravi, Shahriar Faghani, et al.. (2022). Mitigating Bias in Radiology Machine Learning: 1. Data Handling. Radiology Artificial Intelligence. 4(5). e210290–e210290. 81 indexed citations

11.

Zhang, Kuan, Haoji Hu, Kenneth A. Philbrick, et al.. (2022). SOUP-GAN: Super-Resolution MRI Using Generative Adversarial Networks. Tomography. 8(2). 905–919. 64 indexed citations

12.

Moassefi, Mana, Shahriar Faghani, Gian Marco Conte, et al.. (2022). A deep learning model for discriminating true progression from pseudoprogression in glioblastoma patients. Journal of Neuro-Oncology. 159(2). 447–455. 27 indexed citations

13.

Lombardi, Carlo, Elena Roca, Barbara Bigni, et al.. (2021). Immune and cellular damage biomarkers to predict COVID-19 mortality in hospitalized patients. SHILAP Revista de lepidopterología. 2. 155–162. 3 indexed citations

14.

Conte, Gian Marco, Alexander D. Weston, Kenneth A. Philbrick, et al.. (2021). Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model. Radiology. 299(2). 313–323. 76 indexed citations

15.

Sferruzza, Giacomo, Teresa Calimeri, Sara Steffanoni, et al.. (2021). Quantitative muscle mass biomarkers are independent prognosis factors in primary central nervous system lymphoma: The role of L3-skeletal muscle index and temporal muscle thickness. European Journal of Radiology. 143. 109945–109945. 19 indexed citations

16.

Cai, Jason, Zeynettin Akkus, Kenneth A. Philbrick, et al.. (2020). Fully Automated Segmentation of Head CT Neuroanatomy Using Deep Learning. Radiology Artificial Intelligence. 2(5). e190183–e190183. 29 indexed citations

17.

Conte, Gian Marco, Luisa Altabella, Antonella Castellano, et al.. (2019). Comparison of T1 mapping and fixed T1 method for dynamic contrast-enhanced MRI perfusion in brain gliomas. European Radiology. 29(7). 3467–3479. 24 indexed citations

18.

Conte, Gian Marco, Antonella Castellano, Luisa Altabella, et al.. (2017). Reproducibility of dynamic contrast-enhanced MRI and dynamic susceptibility contrast MRI in the study of brain gliomas: a comparison of data obtained using different commercial software. La radiologia medica. 122(4). 294–302. 22 indexed citations

19.

Castellano, Antonella, Gian Marco Conte, Marcello Cadioli, et al.. (2016). Dynamic contrast-enhanced and dynamic susceptibility contrast perfusion MR imaging for glioma grading: Preliminary comparison of vessel compartment and permeability parameters using hotspot and histogram analysis. European Journal of Radiology. 85(6). 1147–1156. 69 indexed citations

20.

Sartório, Alessandro, Gian Marco Conte, Antonio Conti, et al.. (2000). Effects of 12 months rec-GH therapy on bone and collagen turnover and bone mineral density in GH deficient children with thalassaemia major. Journal of Endocrinological Investigation. 23(6). 356–361. 13 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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