Luca Giancardo

3.3k total citations · 1 hit paper
82 papers, 1.9k citations indexed

About

Luca Giancardo is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Epidemiology. According to data from OpenAlex, Luca Giancardo has authored 82 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Radiology, Nuclear Medicine and Imaging, 26 papers in Ophthalmology and 21 papers in Epidemiology. Recurrent topics in Luca Giancardo's work include Retinal Imaging and Analysis (29 papers), Retinal Diseases and Treatments (21 papers) and Acute Ischemic Stroke Management (21 papers). Luca Giancardo is often cited by papers focused on Retinal Imaging and Analysis (29 papers), Retinal Diseases and Treatments (21 papers) and Acute Ischemic Stroke Management (21 papers). Luca Giancardo collaborates with scholars based in United States, Italy and France. Luca Giancardo's co-authors include Fabrice Mériaudeau, Edward Chaum, Thomas P. Karnowski, Kenneth W. Tobin, Seema Garg, Yaqin Li, Samiksha Pachade, Manesh Kokare, Prasanna Porwal and Sunil A. Sheth and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Luca Giancardo

76 papers receiving 1.8k 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.

Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research

2021 157 citations Samiksha Pachade, Prasanna Porwal et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Luca Giancardo United States	24	1.1k	728	453	255	229	82	1.9k
Ulrich Schiefer Germany	31	963 0.9×	1.6k 2.2×	71 0.2×	822 3.2×	276 1.2×	166	2.7k
J. van der Steen Netherlands	30	315 0.3×	729 1.0×	86 0.2×	474 1.9×	175 0.8×	118	3.0k
Julia P. Owen United States	31	1.1k 1.0×	167 0.2×	44 0.1×	204 0.8×	145 0.6×	61	2.6k
Timothy J. Gawne United States	25	697 0.6×	488 0.7×	62 0.1×	731 2.9×	34 0.1×	70	2.1k
Benjamin Thompson Canada	43	549 0.5×	1.6k 2.2×	70 0.2×	3.0k 11.6×	73 0.3×	247	5.9k
Michelle Yan United States	9	481 0.4×	80 0.1×	161 0.4×	35 0.1×	47 0.2×	17	1.3k
Raymond P. Najjar Singapore	23	459 0.4×	475 0.7×	28 0.1×	283 1.1×	95 0.4×	67	1.6k
William H. Swanson United States	30	1.3k 1.2×	1.9k 2.6×	64 0.1×	548 2.1×	47 0.2×	114	3.1k
Elizabeth L. Irving Canada	23	774 0.7×	792 1.1×	57 0.1×	1.0k 4.1×	56 0.2×	132	2.1k
Allison M. McKendrick Australia	34	1.3k 1.2×	1.9k 2.7×	95 0.2×	587 2.3×	61 0.3×	193	3.5k

Countries citing papers authored by Luca Giancardo

Since Specialization

Citations

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

Fields of papers citing papers by Luca Giancardo

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luca Giancardo

This figure shows the co-authorship network connecting the top 25 collaborators of Luca Giancardo. A scholar is included among the top collaborators of Luca Giancardo 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 Luca Giancardo. Luca Giancardo 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

Roberts, Kirk, et al.. (2025). A Multi-Modal Pelvic MRI Dataset for Deep Learning-Based Pelvic Organ Segmentation in Endometriosis. Scientific Data. 12(1). 1292–1292.

Xie, Ziqian, Hao Yuan, Yaochen Xie, et al.. (2024). Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging. Communications Biology. 7(1). 414–414. 12 indexed citations

Oliver, Arnau, et al.. (2024). Strategies to combine 3D vasculature and brain CTA with deep neural networks: Application to LVO. iScience. 27(2). 108881–108881.

Pachade, Samiksha, et al.. (2024). Generalizable self-supervised learning for brain CTA in acute stroke. Computers in Biology and Medicine. 184. 109337–109337. 1 indexed citations

Coronado, Ivan, Samiksha Pachade, Emanuele Trucco, et al.. (2023). Synthetic OCT-A blood vessel maps using fundus images and generative adversarial networks. Scientific Reports. 13(1). 15325–15325. 3 indexed citations

Pachade, Samiksha, Surabhi Datta, Yi Dong, et al.. (2023). Self-Supervised Learning with Radiology Reports, A Comparative Analysis of Strategies for Large Vessel Occlusion and Brain CTA Images. PubMed. 2023. 1–5. 3 indexed citations

Giancardo, Luca, et al.. (2022). Keystroke-Dynamics for Parkinson's Disease Signs Detection in an At-Home Uncontrolled Population: A New Benchmark and Method. IEEE Transactions on Biomedical Engineering. 70(1). 182–192. 20 indexed citations

Pachade, Samiksha, Ivan Coronado, Rania Abdelkhaleq, et al.. (2022). Detection of Stroke with Retinal Microvascular Density and Self-Supervised Learning Using OCT-A and Fundus Imaging. Journal of Clinical Medicine. 11(24). 7408–7408. 14 indexed citations

Xie, Ziqian, et al.. (2022). Issues in Melanoma Detection: Semisupervised Deep Learning Algorithm Development via a Combination of Human and Artificial Intelligence. JMIR Dermatology. 5(4). e39113–e39113. 1 indexed citations

10.

Holcomb, Jennifer, et al.. (2022). Predicting health-related social needs in Medicaid and Medicare populations using machine learning. Scientific Reports. 12(1). 4554–4554. 17 indexed citations

11.

Salazar‐Marioni, Sergio, Fabien Scalzo, Mudassir Farooqui, et al.. (2022). Quantification of infarct core signal using CT imaging in acute ischemic stroke. NeuroImage Clinical. 34. 102998–102998. 8 indexed citations

12.

Sujit, Sheeba J., et al.. (2021). Deep learning enabled brain shunt valve identification using mobile phones. Computer Methods and Programs in Biomedicine. 210. 106356–106356. 5 indexed citations

13.

Barman, Arko, et al.. (2021). Novel Autosegmentation Spatial Similarity Metrics Capture the Time Required to Correct Segmentations Better Than Traditional Metrics in a Thoracic Cavity Segmentation Workflow. Journal of Digital Imaging. 34(3). 541–553. 28 indexed citations

14.

Pachade, Samiksha, Prasanna Porwal, Manesh Kokare, Luca Giancardo, & Fabrice Mériaudeau. (2021). NENet: Nested EfficientNet and adversarial learning for joint optic disc and cup segmentation. Medical Image Analysis. 74. 102253–102253. 47 indexed citations

15.

Crimi, Alessandro, Luca Giancardo, Fabio Sambataro, et al.. (2019). MultiLink Analysis: Brain Network Comparison via Sparse Connectivity Analysis. Scientific Reports. 9(1). 65–65. 9 indexed citations

16.

Barman, Arko, et al.. (2019). Quantifying Neurodegenerative Progression With DeepSymNet, an End-to-End Data-Driven Approach. Frontiers in Neuroscience. 13. 1053–1053. 8 indexed citations

17.

Montero, Paloma, Michele Matarazzo, José Á. Obeso, et al.. (2016). Computer keyboard interaction as an indicator of early Parkinson’s disease. Nature. 1 indexed citations

18.

Giancardo, Luca, Álvaro Sánchez‐Ferro, I. Butterworth, Carlos S. Mendoza, & Jacob M. Hooker. (2015). Psychomotor Impairment Detection via Finger Interactions with a Computer Keyboard During Natural Typing. Scientific Reports. 5(1). 9678–9678. 27 indexed citations

19.

Giancardo, Luca, Fabrice Mériaudeau, Thomas P. Karnowski, et al.. (2011). Automatic Diabetic Macular Edema Detection in Fundus Images Using Publicly Available Datasets. Medical Image Analysis. 1 indexed citations

20.

Santos-Villalobos, Hector, Thomas P. Karnowski, Deniz Aykac, et al.. (2011). Statistical characterization and segmentation of drusen in fundus images. PubMed. 46. 6236–6241. 10 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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