Filippo Molinari

11.9k total citations · 5 hit papers
311 papers, 8.5k citations indexed

About

Filippo Molinari is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Filippo Molinari has authored 311 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Pulmonary and Respiratory Medicine, 94 papers in Radiology, Nuclear Medicine and Imaging and 92 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Filippo Molinari's work include Cardiovascular Health and Disease Prevention (73 papers), Cerebrovascular and Carotid Artery Diseases (70 papers) and AI in cancer detection (39 papers). Filippo Molinari is often cited by papers focused on Cardiovascular Health and Disease Prevention (73 papers), Cerebrovascular and Carotid Artery Diseases (70 papers) and AI in cancer detection (39 papers). Filippo Molinari collaborates with scholars based in Italy, Singapore and United States. Filippo Molinari's co-authors include U. Rajendra Acharya, Jasjit S. Suri, Massimo Salvi, Kristen M. Meiburger, Guang Zeng, S. Vinitha Sree, Prabal Datta Barua, Nicola Michielli, Hui Wen Loh and Oliver Faust and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Filippo Molinari

295 papers receiving 8.2k citations

Hit Papers

Automated diagnosis of epileptic EEG using entropies 2011 2026 2016 2021 2011 2022 2019 2020 2023 100 200 300 400
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.

  1. Automated diagnosis of epileptic EEG using entropies
    2011 468 citations U. Rajendra Acharya, Filippo Molinari et al. profile →
  2. Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
    2022 438 citations Silvia Seoni, Prabal Datta Barua et al. profile →
  3. Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals
    2019 289 citations Nicola Michielli, U. Rajendra Acharya et al. profile →
  4. The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
    2020 242 citations Massimo Salvi, U. Rajendra Acharya et al. profile →
  5. Application of uncertainty quantification to artificial intelligence in healthcare: A review of last decade (2013–2023)
    2023 97 citations Silvia Seoni, Massimo Salvi et al. profile →

Peers

Filippo Molinari
Dimitrios I. Fotiadis Greece
Yuanyuan Wang China
Ayman El‐Baz United States
E. Y. K. Ng Singapore
Guang Yang United Kingdom
Jasjit S. Suri United States
Ru‐San Tan Singapore
Konstantina S. Nikita Greece
Namkug Kim South Korea
Muhammad E. H. Chowdhury Qatar
Dimitrios I. Fotiadis Greece
Filippo Molinari
Citations per year, relative to Filippo Molinari Filippo Molinari (= 1×) peers Dimitrios I. Fotiadis

Countries citing papers authored by Filippo Molinari

Since Specialization
Citations

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

Fields of papers citing papers by Filippo Molinari

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Filippo Molinari

This figure shows the co-authorship network connecting the top 25 collaborators of Filippo Molinari. A scholar is included among the top collaborators of Filippo Molinari 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 Filippo Molinari. Filippo Molinari 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.
Salvi, Massimo, Silvia Seoni, Andrea Campagner, et al.. (2025). Explainability and uncertainty: Two sides of the same coin for enhancing the interpretability of deep learning models in healthcare. International Journal of Medical Informatics. 197. 105846–105846. 14 indexed citations
2.
Sciancalepore, Francesco, Roberta Balestrino, Iva Stanković, et al.. (2025). Multi-Center 3D CNN for Parkinson’s disease diagnosis and prognosis using clinical and T1-weighted MRI data. NeuroImage Clinical. 48. 103859–103859.
3.
Rosini, Elena, et al.. (2025). Valuable Compounds from Pollutants: Converting PET into Enantiopure Alanine. ACS Catalysis. 15(21). 17829–17843.
4.
Torre, Carolina de la, et al.. (2025). A cascade approach for the early detection and localization of myocardial infarction in 2D-echocardiography. Medical Engineering & Physics. 143(1). 104400–104400.
5.
Gudigar, Anjan, U. Raghavendra, Massimo Salvi, et al.. (2025). A Dual-Stream Deep Learning Architecture With Adaptive Random Vector Functional Link for Multi-Center Ischemic Stroke Classification. IEEE Access. 13. 46638–46658. 2 indexed citations
6.
Chakraborty, Subrata, Silvia Seoni, Massimo Salvi, et al.. (2024). Artificial Intelligence-Based Suicide Prevention and Prediction: A Systematic Review (2019-2023). SSRN Electronic Journal. 3 indexed citations
7.
Salvi, Massimo, Nicola Michielli, Alessandro Gambella, et al.. (2024). Computational Synthesis of Histological Stains: A Step Toward Virtual Enhanced Digital Pathology. International Journal of Imaging Systems and Technology. 34(5). 1 indexed citations
8.
Santis, Riccardo De, Giovanni Faggioni, Andrea Ciammaruconi, et al.. (2023). Durability of neutralizing antibodies against yellow fever virus after vaccination in healthy adults. Vaccine. 41(17). 2761–2763. 5 indexed citations
9.
Manna, Antonio, Nicola Pasculli, Florigio Lista, et al.. (2023). SARS-CoV-2 Inactivation in Aerosol by Means of Radiated Microwaves. Viruses. 15(7). 1443–1443. 6 indexed citations
10.
Raghavendra, U., Anjan Gudigar, Massimo Salvi, et al.. (2023). A Novel Attention-Based Model for Semantic Segmentation of Prostate Glands Using Histopathological Images. IEEE Access. 11. 108982–108994. 7 indexed citations
11.
Gambella, Alessandro, Massimo Salvi, Luca Molinaro, et al.. (2023). Improved assessment of donor liver steatosis using Banff consensus recommendations and deep learning algorithms. Journal of Hepatology. 80(3). 495–504. 6 indexed citations
12.
Raghavendra, U., Anjan Gudigar, Ajay Hegde, et al.. (2023). YOLOv5s-CAM: A Deep Learning Model for Automated Detection and Classification for Types of Intracranial Hematoma in CT Images. IEEE Access. 11. 141309–141328. 5 indexed citations
13.
Salvi, Massimo, et al.. (2023). cyto‐Knet: An instance segmentation approach for multiple myeloma plasma cells using conditional kernels. International Journal of Imaging Systems and Technology. 34(1). 5 indexed citations
14.
Gudigar, Anjan, U. Raghavendra, Krishnananda Nayak, et al.. (2022). Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques. Journal of Imaging. 8(4). 102–102. 9 indexed citations
15.
Gudigar, Anjan, U. Raghavendra, Ajay Hegde, et al.. (2021). Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives. International Journal of Environmental Research and Public Health. 18(12). 6499–6499. 44 indexed citations
16.
Gudigar, Anjan, Jyothi Samanth, U. Raghavendra, et al.. (2020). Local Preserving Class Separation Framework to Identify Gestational Diabetes Mellitus Mother Using Ultrasound Fetal Cardiac Image. IEEE Access. 8. 229043–229051. 11 indexed citations
17.
Balestra, Gabriella, Marco Knaflitz, & Filippo Molinari. (2002). Principles of Statistical Gait Analysis. PORTO Publications Open Repository TOrino (Politecnico di Torino). 3 indexed citations
18.
Ceravolo, Rosario, et al.. (1999). Identificazione Strutturale a Input Incognito mediante Estimatori di Ampiezza e Fase Istantanea. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
19.
Ceravolo, Rosario, et al.. (1999). Identificazione Diretta e Indiretta a Input Incognito di Edifici in Muratura. PORTO Publications Open Repository TOrino (Politecnico di Torino). 1 indexed citations
20.
Bonato, Paolo, Rosario Ceravolo, Alessandro De Stefano, & Filippo Molinari. (1998). A New Cross-Time-Frequency Method for the Structural Identification of Mechanical Systems in Non-Stationary Conditions. PORTO Publications Open Repository TOrino (Politecnico di Torino). 2 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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