Journals

• Kosar Haghshenas, Ali Pahlevan, Marina Zapater Sancho, Siamak Mohammadi, David Atienza, "MAGNETIC: Multi-Agent Machine Learning-Based Approach for Energy Efficient Dynamic Consolidation in Data Centers", IEEE Transactions on Services Computing, May 2019, DOI: 10.1109/TSC.2019.2919555
• Farnaz Forooghifar, Amir Aminifar, David Atienza Alonso, "Resource-Aware Distributed Epilepsy Monitoring Using Self-Awareness From Edge to Cloud", IEEE Transactions on Biomedical Circuits and Systems, Vol. 13, No. 6, pp. 1338 - 1350, Dec. 2019, DOI: 10.1109/TBCAS.2019.2951222
• Iacopo Colonnelli, Barbara Cantalupo, Ivan Merelli, Marco Aldinucci, "StreamFlow: cross-breeding cloud with HPC", in IEEE Transactions on Emerging Topics in Computing, vol. 9, no. 4, pp. 1723-1737, 1 Oct.-Dec. 2021, doi: 10.1109/TETC.2020.3019202.
• Enzo Tartaglione, Carlo Alberto Barbano, Claudio Berzovini, Marco Calandri, Marco Grangetto, "Unveiling COVID-19 from Chest X-ray with deeplearning: a hurdles race with small data", June 2020, DOI: 10.5281/zenodo.3888049
• Elisabetta de Giovanni; Fabio Montagna; Benoit Denkinger; Simone Machetti; Miguel Peón-Quirós; Simone Benatti; Davide Rossi; Luca Benini; David Atienza; "Modular Design and Optimization of Biomedical Applications for Ultra-Low Power Heterogeneous Platforms", in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39, no. 11, pp. 3821-3832, Nov. 2020, doi: 10.1109/TCAD.2020.3012652
• Gianluca Bontempi; Ricardo Chavarriaga; Hans eD Canck; Emanuela Girardi; Marco Aldinucci; et al.; "The CLAIRE COVID-19 initiative: approach, experiences and recommendations", in Ethics Inf Technol 23 (Suppl 1), 127–133 (2021), Feb. 2021. https://doi.org/10.1007/s10676-020-09567-7
• Daniele D'Agostino; Pietro Liò; Marco Aldinucci; Ivan Merelli; "Advantages of using graph databases to explore chromatin conformation capture experiments", in BMC Bioinformatics 22 (Suppl 2), 43 (2021), Apr. 2021. https://doi.org/10.1186/s12859-020-03937-0
• Gabeff, Valentin; Teijeiro, Tomas; Zapater, Marina; Cammoun, Leila; Rheims, Sylvain; Ryvlin, Philippe; Atienza, David; "Interpreting deep learning models for epileptic seizure detection on EEG signals", in Artificial Intelligence in Medicine, Elsevier, Volume 117, July 2021, DOI: 10.1016/j.artmed.2021.102084
• Pennisi, Matteo; Kavasidis, Isaak; Spampinato, Concetto; Schinina, Vincenzo; Palazzo, Simone; Proietto Salanitri, Federica; Bellitto, Giovanni; Rundo, Francesco; Aldinucci, Marco; Cristofaro, Massimo; Campioni, Paolo; Pianura, Elisa; Di Stefano, Federica; Petrone, Ada; Albarello, Fabrizio; Ippolito, Giuseppe; Cuzzocrea, Salvatore; Conoci, Sabrina; "An explainable AI system for automated COVID-19 assessment and lesion categorization from CT-scans", in Artificial Intelligence in Medicine, Elsevier, Volume 118, August 2021, DOI: 10.1016/j.artmed.2021.102114
• Tartaglione, Enzo; Bragagnolo, Andrea; Odierna, Francesco; Fiandrotti, Attilio; Grangetto, Marco; "SeReNe: Sensitivity based Regularization of Neurons for Structured Sparsity in Neural Networks", in IEEE Transactions on Neural Networks and Learning Systems, June 2021, DOI: 10.1109/TNNLS.2021.3084527
• Orlandic, Lara; Teijeiro, Tomas; Atienza, David; "The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms ", in Sci Data 8, 156 (2021), June 2021. https://doi.org/10.1038/s41597-021-00937-4
• Baghersalimi, Saleh; Teijeiro, Tomas; Atienza, David; Aminifar, Amir; "Personalized Real-Time Federated Learning for Epileptic Seizure Detection", in IEEE Journal of Biomedical and Health Informatics, vol. 26, no. 2, pp. 898-909, Feb. 2022, DOI: 10.1109/JBHI.2021.3096127
• Cipriano, Marco; Allegretti, Stefano; Bolelli, Federico; Di Bartolomeo, Mattia; Pollastri, Federico; Pellacani, Arrigo; Minafra, Paolo; Anesi, Alexandre; Grana, Costantino; "Deep Segmentation of the Mandibular Canal: A New 3D Annotated Dataset of CBCT Volumes", in IEEE Access, vol. 10, pp. 11500-11510, Jan. 2022, DOI: 10.1109/ACCESS.2022.3144840
• Iacopo Colonnelli; Marco Aldinucci; Barbara Cantalupo; et al.; "Distributed workflows with Jupyter", in Future Generation Computer Systems, Elsevier, Volume 128, p. 282-298, Mar. 2022, DOI: 10.1016/j.future.2021.10.007
• Pollastri, Federico; Parreño, Mario; Maroñas, Juan; Bolelli, Federico; Paredes, Roberto; Ramos, Daniel; Grana Costantino; "A deep analysis on high-resolution dermoscopic image classification", in IET Comput. Vis., 15( 7), 514– 526 (2021), Apr. 2021. https://doi.org/10.1049/cvi2.12048
• De Giovanni, Elisabetta; Teijeiro, Tomas; P. Millet, Gregoire; Atienza, David; "Adaptive R-Peak Detection on Wearable ECG Sensors for High-Intensity Exercise " in IEEE Transactions on Biomedical Engineering, Sept. 2022, DOI: 10.1109/TBME.2022.3205304

Conferences

• Monica Caballero, Jon Ander Gómez, Aimilia Bantouna, “Deep-Learning and HPC to Boost Biomedical Applications for Health (DeepHealth)”, 2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), June 2019, DOI: 10.1109/CBMS.2019.00040
• Anthony Hitchcock Thomas, Amir Aminifar, David Atienza, "Noise-Resilient and Interpretable Epileptic Seizure Detection", IEEE International Symposium on Circuits and Systems (ISCAS 2020), Seville, Spain, May 2020,DOI: 10.5281/zenodo.3903314
• Silvio Zanoli, Tomas Teijeiro, Fabio Montagna, David Atienza, "An Event-Based System for Low-Power ECG QRS Complex Detection", Design, Automation & Test in Europe Conference & Exhibition (DATE) 2020, Grenoble, France, March 2020, , pp. 258-263, DOI: 10.23919/DATE48585.2020.9116498
• Teijeiro, Tomas; "Knowledge, Machine Learning and Atrial Fibrillation: More Ingredients for a Tastier Cocktail", Computing in Cardiology (CinC), Rimini, Italy, 13-16 September 2020, DOI: 10.22489/CinC.2020.476
• Versaci, Francesco; "WaveTF: A Fast 2D Wavelet Transform for Machine Learning in Keras", Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science(), vol 12661. Springer, Cham. https://doi.org/10.1007/978-3-030-68763-2_46
• Iacopo Colonnelli; Barbara Cantalupo; Roberto Esposito; Matteo Pennisi; Concetto Spampinato; Marco Aldinucci; "HPC Application Cloudification: The StreamFlow Toolkit", 12th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and 10th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2021), Budapest, HU (Virtual), 19 January 2021, DOI: 10.4230/OASIcs.PARMA-DITAM.2021.5
• Pino, Carmelo; Palazzo, Simone; Trenta, Francesca; Cordero, Francesca; Bagci, Ulas; Rundo, Francesco; Battiato, Sebastiano; Giordano, Daniela; Aldinucci, Marco; Spampinato, Concetto; "Interpretable deep model for predicting gene-addicted non-small-cell lung cancer in CT scans", 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 13-16 April 2021, pp. 891-894, DOI: 10.1109/ISBI48211.2021.9433832
• Iacopo Colonnelli; Barbara Cantalupo; Concetto Spampinato; Matteo Pennisi; Marco Aldinucci; "Bringing AI pipelines onto cloud-HPC: setting a baseline for accuracy of COVID-19 diagnosis", in ENEA CRESCO in the fight against COVID-19, ENEA, Virtual, pp. 66-73 (978-88-8286-415-6), Jan.26th – Feb. 23rd 2021
• Daniele Perlo; Enzo Tartaglione; Luca Bertero; Paola Cassoni; Marco Grangetto; "Dysplasia Grading of Colorectal Polyps Through Convolutional Neural Network Analysis of Whole Slide Images", In: Su, R., Zhang, YD., Liu, H. (eds) Proceedings of 2021 International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2021). MICAD 2021. Lecture Notes in Electrical Engineering, vol 784. Springer, Singapore. https://doi.org/10.1007/978-981-16-3880-0_34
• Carlo Alberto Barbano; Daniele Perlo; Enzo Tartaglione; Attilio Fiandrotti; Luca Bertero; Paola Cassoni; Marco Grangetto; "Unitopatho, A Labeled Histopathological Dataset for Colorectal Polyps Classification and Adenoma Dysplasia Grading", 2021 IEEE International Conference on Image Processing (ICIP), 19-22 September 2021, pp. 76-80, DOI: 10.1109/ICIP42928.2021.9506198
• Jean-Philippe Poli; Wassila Ouerdane; Régis Pierrard; "Generation of Textual Explanations in XAI: the Case of Semantic Annotation", 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 11-14 July 2021, pp. 1-6, DOI: 10.1109/FUZZ45933.2021.9494589.
• Francesco Versaci; Giovanni Busonera; "Scaling deep learning data management with Cassandra DB", 2021 IEEE International Conference on Big Data (Big Data), 15-18 December 2021, pp. 5301-5310, DOI: 10.1109/BigData52589.2021.9672005
• Chaudhry, Hafiza Ayesha Hoor; Renzulli, Riccardo; Perlo Daniele; Santinelli, Francesca; Tibaldi, Stefano; Cristiano, Carmen; Grosso, Marco; Limerutti, Giorgio; Fiandrotti, Attilio; Grangetto, Marco; Fonio; "UniToChest: A Lung Image Dataset for Segmentation of Cancerous Nodules on CT Scans", In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13231. Springer, Cham. https://doi.org/10.1007/978-3-031-06427-2_16
• Barbano, Carlo Alberto; Tartaglione, Enzo; Berzovini, Claudio; Calandri, Marco; Grangetto, Marco; "A Two-Step Radiologist-Like Approach for Covid-19 Computer-Aided Diagnosis from Chest X-Ray Images", In: Sclaroff, S., Distante, C., Leo, M., Farinella, G.M., Tombari, F. (eds) Image Analysis and Processing – ICIAP 2022. ICIAP 2022. Lecture Notes in Computer Science, vol 13231. Springer, Cham. https://doi.org/10.1007/978-3-031-06427-2_15
• Canalini, Laura; Pollastri, Federico; Bolelli, Federico; Cancilla Michele; Allegretti, Stefano; Grana, Costantino; "Skin Lesion Segmentation Ensemble with Diverse Training Strategies", In: Vento, M., Percannella, G. (eds) Computer Analysis of Images and Patterns. CAIP 2019. Lecture Notes in Computer Science(), vol 11678. Springer, Cham. https://doi.org/10.1007/978-3-030-29888-3_8

Book Chapters

• Jon A. Gómez; Marco Aldinucci; David Atienza, David; et al.; "The DeepHealth Toolkit: A Key European Free and Open-Source Software for Deep Learning and Computer Vision Ready to Exploit Heterogeneous HPC and Cloud Architectures", In: Curry, E., Auer, S., Berre, A.J., Metzger, A., Perez, M.S., Zillner, S. (eds) Technologies and Applications for Big Data Value . Springer, Cham. https://doi.org/10.1007/978-3-030-78307-5_9
• Monica Caballero; Marco Aldinucci; Jon Ander Gómez; et al.; "HPC, Big Data, and AI Convergence Towards Exascale: Challenge and Vision, by Olivier Terzo and Jan Martinovič (DeepHealth contribution)"

Preprints

• J. M. Saborit-Torres; J. J. Saenz-Gamboa; J. À. Montell; J. M. Salinas; J. A. Gómez; I. Stefan; M. Caparrós; F. García-García; J. Domenech; J. V. Manjón; G. Rojas; A. Pertusa; A. Bustos; G. González; J. Galant; M. de la Iglesia-Vayá; "Medical imaging data structure extended to multiple modalities and anatomical regions"
• Irene Pérez-Díez; Raúl Pérez-Moraga; Adolfo López-Cerdán; Marisa Caparrós Redondo; Jose-Maria Salinas-Serrano; María de la Iglesia-Vayá; "De-identifying Spanish medical texts - Named Entity Recognition applied to radiology reports"
• Umberto Amedeo Gava; Federico D'Agata; Enzo Tartaglione; Marco Grangetto; Francesca Bertolino; Ambra Santonocito; Edwin Bennink; Mauro Bergui; "Neural Network-derived perfusion maps: a Model-free approach to computed tomography perfusion in patients with acute ischemic stroke"

Other

• Jon Ander Gómez, Monica Caballero, “DeepHealth project: Deep-learning and HPC to boost biomedical applications for health”, Open Access Government, October 2019
• Aldinucci; Berzovini; Grana; Grangetto; Pireddu; Zanetti, “Deep Learning e calcolo ad alte prestazioni per l'elaborazione di immagini biomediche”, Convegno Nazionale Italiano sull'Intelligenza Artificiale (Ital-IA), March 2019, DOI: 10.5281/zenodo.3338256
• Cardillo, Franco Alberto; "Baselines for automatic medical image reporting", 1st Serbian International Conference on Applied Artificial Intelligence (SICAAI), Kragujevac, Serbia, May 19-20, 2022