Fondazione DARE

Bibliografia

In questa sezione puoi consultare le pubblicazioni finanziate dal progetto DARE. 

Di Chiano, M., Rocchetti, M. T., Spano, G., Russo, P., Allegretta, C., Milior, G., Gadaleta, R. M., Sallustio, F., Pontrelli, P., Gesualdo, L., Avolio, C., Fiocco, D., & Gallone, A. (2024). Lactobacilli Cell-Free Supernatants Modulate Inflammation and Oxidative Stress in Human Microglia via NRF2-SOD1 Signaling. Cellular and Molecular Neurobiology, 44(1), 60. https://doi.org/10.1007/s10571-024-01494-1
Dentamaro, V., Impedovo, D., Musti, L., Pirlo, G., & Taurisano, P. (2024). Enhancing early Parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database. Scientific Reports, 14(1), 20941. https://doi.org/10.1038/s41598-024-70165-4
Falvino, A., Gasperini, B., Cariati, I., Bonanni, R., Chiavoghilefu, A., Gasbarra, E., Botta, A., Tancredi, V., & Tarantino, U. (2024). Cellular Senescence: The Driving Force of Musculoskeletal Diseases. Biomedicines, 12(9), 1948. https://doi.org/10.3390/biomedicines12091948
Simionato, D., Collesei, A., Miglietta, F., & Vandin, F. (2024). ALLSTAR : inference of reliAble causaL ruLes between Somatic muTAtions and canceR phenotypes. Bioinformatics, 40(7), btae449. https://doi.org/10.1093/bioinformatics/btae449
Amato, D., Calderaro, S., Lo Bosco, G., Rizzo, R., & Vella, F. (2024). Explainable Histopathology Image Classification with Self-organizing Maps: A Granular Computing Perspective. Cognitive Computation. https://doi.org/10.1007/s12559-024-10312-1
Cantarutti, A., Rescigno, P., Da Borso, C., Gutierrez De Rubalcava Doblas, J., Bressan, S., Barbieri, E., Giaquinto, C., & Canova, C. (2024). Association Between Early-Life Exposure to Antibiotics and Development of Child Obesity: Population-Based Study in Italy. JMIR Public Health and Surveillance, 10, e51734. https://doi.org/10.2196/51734
Basile, A., Calefato, F., Lanubile, Filippo, Mallardi, G., & Quaranta, L. (2024, May 29). An MLOps Solution Framework for Transitioning Machine Learning Models into eHealth Systems. Ital-IA 2024: 4th National Conference on Artificial Intelligencee, organized by CINI, Napoli, Italia. https://ceur-ws.org/Vol-3762/524.pdf
Calefato, F., Quaranta, L., & Lanubile, F. (2024). A Lot of Talk and a Badge: An Exploratory Analysis of Personal Achievements in GitHub. Information and Software Technology, 176, 107561. https://doi.org/10.1016/j.infsof.2024.107561
Orlando, S., Cicala, M., DeSanto, C., Mosconi, C., Ciccacci, F., Guarente, L., Carestia, M., Liotta, G., Di Giovanni, D., Buonomo, E., Riccardi, F., Palombi, L., & Emberti Gialloreti, L. (2024). The financial burden of healthcare- associated infections: A propensity score analysis in an Italian healthcare setting. Infection Prevention in Practice, 100406. https://doi.org/10.1016/j.infpip.2024.100406
Caracausi, M., Ramacieri, G., Catapano, F., Cicilloni, M., Lajin, B., Pelleri, M. C., Piovesan, A., Vitale, L., Locatelli, C., Pirazzoli, G. L., Strippoli, P., Antonaros, F., & Vione, B. (2024). The functional roles of S‐adenosyl‐methionine and S‐adenosyl‐homocysteine and their involvement in trisomy 21. BioFactors, 50(4), 709–724. https://doi.org/10.1002/biof.2044
Caputo, M., Tricase, A., Marchianò, V., Scandurra, C., Piscitelli, M., Sarcina, L., Catacchio, M., Di Franco, C., Bollella, P., Torsi, L., & Macchia, E. (2024). Perspectives on systematic optimization of ultrasensitive biosensors through experimental design. Journal of Materials Chemistry C, 12(38), 15382–15400. https://doi.org/10.1039/D4TC02131B
Bernardini, S., Onnivello, S., & Lanfranchi, S. (2024). Italian normative data for the Unhelpful Thoughts and Beliefs about Stuttering (UTBAS) Scales for adults who stutter. Journal of Fluency Disorders, 81. Scopus. https://doi.org/10.1016/j.jfludis.2024.106074
Lawn, T., Giacomel, A., Martins, D., Veronese, M., Howard, M., Turkheimer, F. E., & Dipasquale, O. (2024). Normative modelling of molecular-based functional circuits captures clinical heterogeneity transdiagnostically in psychiatric patients. Communications Biology, 7(1). Scopus. https://doi.org/10.1038/s42003-024-06391-3
Kumar, B., Lorusso, E., Fosso, B., & Pesole, G. (2024). A comprehensive overview of microbiome data in the light of machine learning applications: categorization, accessibility, and future directions. Frontiers in Microbiology, 15. Scopus. https://doi.org/10.3389/fmicb.2024.1343572
Maccioni, L., Michelle, C. M., Brusaferri, L., Silvestri, E., Bertoldo, A., Schubert, J. J., Nettis, M. A., Mondelli, V., Howes, O., Turkheimer, F. E., Bottlaender, M., Bodini, B., Stankoff, B., Loggia, M. L., & Veronese, M. (2024). A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging. Frontiers in Neuroscience, 18. Scopus. https://doi.org/10.3389/fnins.2024.1395769
Prinzi, F., Orlando, A., Gaglio, S., & Vitabile, S. (2024). Breast cancer classification through multivariate radiomic time series analysis in DCE-MRI sequences. Expert Systems with Applications, 249. Scopus. https://doi.org/10.1016/j.eswa.2024.123557
Cotugno, N., Neri, A., Sanna, M., Santilli, V., Manno, E. C., Pascucci, G. R., Morrocchi, E., Amodio, D., Ruggiero, A., degl Atti, M. L. C., Barneschi, I., Grappi, S., Cocchi, I., Giacomet, V., Trabattoni, D., Olivieri, G., Bernardi, S., O’Connor, D., Montomoli, E., … Palma, P. (2024). Children with perinatally acquired HIV exhibit distinct immune responses to 4CMenB vaccine. JCI Insight, 9(10). Scopus. https://doi.org/10.1172/jci.insight.177182
D’Ascanio, I., Giannini, G., Baldelli, L., Cani, I., Giannoni, A., Leogrande, G., Lopane, G., Calandra-Buonaura, G., Cortelli, P., Chiari, L., & Palmerini, L. (2024). A method for the synchronization of inertial sensor signals and local field potentials from deep brain stimulation systems. Biomedical Physics and Engineering Express, 10(5). Scopus. https://doi.org/10.1088/2057-1976/ad5e83
Chumin, E. J., Burton, C. P., Silvola, R., Miner, E. W., Persohn, S. C., Veronese, M., & Territo, P. R. (2024). Brain metabolic network covariance and aging in a mouse model of Alzheimer’s disease. Alzheimer’s and Dementia, 20(3), 1538–1549. Scopus. https://doi.org/10.1002/alz.13538
Barà, C., Pernice, R., Catania, C. A., Hilal, M., Porta, A., Humeau-Heurtier, A., & Faes, L. (2024). Comparison of entropy rate measures for the evaluation of time series complexity: Simulations and application to heart rate and respiratory variability. Biocybernetics and Biomedical Engineering, 44(2), 380–392. Scopus. https://doi.org/10.1016/j.bbe.2024.04.004
Desantis, V., Borrelli, P., Panebianco, T., Fusillo, A., Bochicchio, D., Solito, A., Pappagallo, F., Mascolo, A., Ancona, A., Cicco, S., Cerchione, C., Romano, A., Montagnani, M., Ria, R., Vacca, A., & Solimando, A. G. (2024). Comprehensive analysis of clinical outcomes, infectious complications and microbiological data in newly diagnosed multiple myeloma patients: a retrospective observational study of 92 subjects. Clinical and Experimental Medicine, 24(1). Scopus. https://doi.org/10.1007/s10238-024-01411-2
Piccinini, F., Tazzari, M., Tumedei, M. M., Stellato, M., Remondini, D., Giampieri, E., Martinelli, G., Castellani, G., & Carbonaro, A. (2024). Data Science for Health Image Alignment: A User-Friendly Open-Source ImageJ/Fiji Plugin for Aligning Multimodality/Immunohistochemistry/Immunofluorescence 2D Microscopy Images. Sensors, 24(2). Scopus. https://doi.org/10.3390/s24020451
Hoang, M. L., Matrella, G., & Ciampolini, P. (2024). Comparison of Machine Learning Algorithms for Heartbeat Detection Based on Accelerometric Signals Produced by a Smart Bed. Sensors, 24(6). Scopus. https://doi.org/10.3390/s24061900
Onnivello, S., Locatelli, C., Pulina, F., Ramacieri, G., Marcolin, C., Antonaros, F., Vione, B., Catapano, F., & Lanfranchi, S. (2024). Cross-sectional developmental trajectories in the adaptive functioning of children and adolescents with Down syndrome. Research in Developmental Disabilities, 144. Scopus. https://doi.org/10.1016/j.ridd.2023.104641
Mazzola, S., Vittorietti, M., Fruscione, S., De Bella, D. D., Savatteri, A., Belluzzo, M., Ginevra, D., Gioia, A., Costanza, D., Castellone, M. D., Costantino, C., Zarcone, M., Ravazzolo, B., Graziano, G., Mannino, R., Amodio, R., Di Marco, V., Vitale, F., & Mazzucco, W. (2024). Factors Associated with Primary Liver Cancer Survival in a Southern Italian Setting in a Changing Epidemiological Scenario. Cancers, 16(11). Scopus. https://doi.org/10.3390/cancers16112046
Colavito, G., Lanubile, F., Novielli, N., & Quaranta, L. (2024). Impact of data quality for automatic issue classification using pre-trained language models. Journal of Systems and Software, 210. Scopus. https://doi.org/10.1016/j.jss.2023.111838
Colavito, G., Lanubile, F., Novielli, N., & Quaranta, L. (2024). Leveraging GPT-like LLMs to Automate Issue Labeling. Proc. - IEEE/ACM Int. Conf. Min. Softw. Repos., MSR, 469–480. Scopus. https://doi.org/10.1145/3643991.3644903
Macchia, E., Björkström, K., Tewari, A., Eskonen, V., Luukkonen, A., Ghafari, A. M., Sarcina, L., Caputo, M., Tong-Ochoa, N., Kopra, K., Pettersson, F., Gounani, Z., Torsi, L., Härmä, H., & Österbacka, R. (2024). Label-free electronic detection of peptide post-translational modification with functional enzyme-driven assay at the physical limit. Cell Reports Physical Science. Scopus. https://doi.org/10.1016/j.xcrp.2024.101874
Orefice, C., Cardillo, R., Lonciari, I., Zoccante, L., & Mammarella, I. C. (2024). “Picture this from there”: spatial perspective-taking in developmental visuospatial disorder and developmental coordination disorder. Frontiers in Psychology, 15. Scopus. https://doi.org/10.3389/fpsyg.2024.1349851
Macchia, E., Torricelli, F., Caputo, M., Sarcina, L., Scandurra, C., Bollella, P., Catacchio, M., Piscitelli, M., Di Franco, C., Scamarcio, G., & Torsi, L. (2024). Point-Of-Care Ultra-Portable Single-Molecule Bioassays for One-Health. Advanced Materials, 36(13). Scopus. https://doi.org/10.1002/adma.202309705
Marfoglia, A., Nardini, F., Mellone, S., & Carbonaro, A. (2024). Representation of Machine Learning Models to Enhance Simulation Capabilities Within Digital Twins in Personalized Healthcare. IEEE Int. Conf. Pervasive Comput. Commun. Workshops Other Affil. Events, PerCom Workshops, 100–105. Scopus. https://doi.org/10.1109/PerComWorkshops59983.2024.10502444
Prinzi, F., Currieri, T., Gaglio, S., & Vitabile, S. (2024). Shallow and deep learning classifiers in medical image analysis. European Radiology Experimental, 8(1). Scopus. https://doi.org/10.1186/s41747-024-00428-2
Arcobelli, V. A., Moscato, S., Palumbo, P., Marfoglia, A., Nardini, F., Randi, P., Davalli, A., Carbonaro, A., Chiari, L., & Mellone, S. (2024). FHIR-standardized data collection on the clinical rehabilitation pathway of trans-femoral amputation patients. Scientific Data, 11(1), 806. https://doi.org/10.1038/s41597-024-03593-6
Lanubile, F., Martinez-Fernandez, S., & Quaranta, L. (2024). Training Future Machine Learning Engineers: A Project-Based Course on MLOps. IEEE Software, 41(2), 60–67. Scopus. https://doi.org/10.1109/MS.2023.3310768
Carbonaro, A., Marfoglia, A., Nardini, F., & Mellone, S. (2024). Corrigendum: CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization(Front. Digit. Health, (2023), 5, (1322428), 10.3389/fdgth.2023.1322428). Frontiers in Digital Health, 6. Scopus. https://doi.org/10.3389/fdgth.2024.1416390
Italiani, P., Frisoni, G., Moro, G., Carbonaro, A., & Sartori, C. (2024). Evidence, my Dear Watson: Abstractive dialogue summarization on learnable relevant utterances. Neurocomputing, 572. Scopus. https://doi.org/10.1016/j.neucom.2023.127132
Amato, D., Calderaro, S., Lo Bosco, G., Rizzo, R., & Vella, F. (2023). Metric Learning in Histopathological Image Classification: Opening the Black Box. Sensors, 23(13), 6003. https://doi.org/10.3390/s23136003
Moro, G., & Ragazzi, L. (2023). Align-then-abstract representation learning for low-resource summarization. Neurocomputing, 548. Scopus. https://doi.org/10.1016/j.neucom.2023.126356
Notario, E., Visci, G., Fosso, B., Gissi, C., Tanaskovic, N., Rescigno, M., Marzano, M., & Pesole, G. (2023). Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution. Genes, 14(8). Scopus. https://doi.org/10.3390/genes14081567
Frisoni, G., Italiani, P., Salvatori, S., & Moro, G. (2023). Cogito Ergo Summ: Abstractive Summarization of Biomedical Papers via Semantic Parsing Graphs and Consistency Rewards. In Williams B., Chen Y., & Neville J. (Eds.), Proc. AAAI Conf. Artif. Intell., AAAI (Vol. 37, pp. 12781–12789). AAAI Press; Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168014584&partnerID=40&md5=e1ed524e25408b6208e603c5ff8303d6
Sarcina, L., Scandurra, C., Di Franco, C., Caputo, M., Catacchio, M., Bollella, P., Scamarcio, G., Macchia, E., & Torsi, L. (2023). A stable physisorbed layer of packed capture antibodies for high-performance sensing applications. Journal of Materials Chemistry C, 11(27), 9093–9106. Scopus. https://doi.org/10.1039/d3tc01123b
Moro, G., Ragazzi, L., & Valgimigli, L. (2023). Carburacy: Summarization Models Tuning and Comparison in Eco-Sustainable Regimes with a Novel Carbon-Aware Accuracy. In Williams B., Chen Y., & Neville J. (Eds.), Proc. AAAI Conf. Artif. Intell., AAAI (Vol. 37, pp. 14417–14425). AAAI Press; Scopus. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167995147&partnerID=40&md5=0207febe2da6b2afc18631d5c8361e22
Carbonaro, A., Marfoglia, A., Nardini, F., & Mellone, S. (2023). CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization. Frontiers in Digital Health, 5. Scopus. https://doi.org/10.3389/fdgth.2023.1322428
Moro, G., Salvatori, S., & Frisoni, G. (2023). Efficient text-image semantic search: A multi-modal vision-language approach for fashion retrieval. Neurocomputing, 538. Scopus. https://doi.org/10.1016/j.neucom.2023.03.057
Moro, G., Ragazzi, L., & Valgimigli, L. (2023). Graph-Based Abstractive Summarization of Extracted Essential Knowledge for Low-Resource Scenarios. In Gal K., Gal K., Nowe A., Nalepa G.J., Fairstein R., & Radulescu R. (Eds.), Front. Artif. Intell. Appl. (Vol. 372, pp. 1747–1754). IOS Press BV; Scopus. https://doi.org/10.3233/FAIA230460
Arcobelli, V. A., Moscato, S., Marfoglia, A., Nardini, F., Randi, P., Davalli, A., Carbonaro, A., Palumbo, P., Chiari, L., & Mellone, S. (2023). MOTU on FHIR: A preliminary strategy to enable interoperability for retrospective dataset standardization. IEEE EMBS Spec. Topic Conf. Data Sci. Eng. Healthc., Med. Biol., IEEECONF, 81–82. Scopus. https://doi.org/10.1109/IEEECONF58974.2023.10404816
Moro, G., Ragazzi, L., Valgimigli, L., & Molfetta, L. (2023). Retrieve-and-Rank End-to-End Summarization of Biomedical Studies. In Pedreira O. & Estivill-Castro V. (Eds.), Lect. Notes Comput. Sci.: Vol. 14289 LNCS (pp. 64–78). Springer Science and Business Media Deutschland GmbH; Scopus. https://doi.org/10.1007/978-3-031-46994-7_6
Di Franco, C., Piscitelli, M., Macchia, E., Scandurra, C., Catacchio, M., Torsi, L., & Scamarcio, G. (2023). Kelvin probe force microscopy on patterned large-area biofunctionalized surfaces: a reliable ultrasensitive platform for biomarker detection. Journal of Materials Chemistry C, 12(1), 73–79. Scopus. https://doi.org/10.1039/d3tc03110a
Dipasquale, O., Cohen, A., Martins, D., Zelaya, F., Turkheimer, F., Veronese, M., Mehta, M. A., Williams, S. C. R., Yang, B., Banerjee, S., & Wang, Y. (2023). Molecular-enriched functional connectivity in the human brain using multiband multi-echo simultaneous ASL/BOLD fMRI. Scientific Reports, 13(1). Scopus. https://doi.org/10.1038/s41598-023-38573-0
Calefato, F., Quaranta, L., Lanubile, F., & Kalinowski, M. (2023). Assessing the Use of AutoML for Data-Driven Software Engineering. 2023 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), 1–12. https://doi.org/10.1109/ESEM56168.2023.10304796

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Email Ufficio Comunicazione: info@fondazionedare.it

PEC: fondazionedare@pec.it

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Questa ricerca è stata cofinanziata dal Piano Nazionale Complementare PNC-I.1 “Iniziativa di ricerca per le tecnologie e percorsi innovativi in ambito sanitario e assistenziale”, D.D. 931 del 06/06/2022, iniziativa “DARE – Digital lifelong prevention”, codice PNC0000002

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