INTOCADS Laboratory – Intelligent Optimized Computer-Aided Diagnosis Systems for Bioengineers Laboratory

Lab Team

Lab Mission

Setting up the INTelligent Optimized Computer-Aided Diagnosis Systems for bioengineers Laboratory (short INTOCADS) – AREA 4: Data and computational modelling. The laboratory will include a complete facility to design, implement and validate optimized decision support systems by means of the following workflow (materials and methods):
1) acquisition of biosignals and supply of bioimages and biodata for data-driven digital twins to simulate and estimate patient-specific characteristics of diseases;
2) advanced and intelligent techniques for processing and segmenting the available materials (biosignals,
bioimages, biodata and biomarkers) and forming the biopatterns;
3) intelligent and optimized methodologies for multifactorial and combined biopattern identification
(radiomic and radiogenomic feature extraction, reduction and transformation);
4) modelling, implementation, training and validation of machine/deep learning optimized topology for
providing Decision Support and Computer Aided Decision/Diagnosis Systems;
5) classification, characterization, staging and grading of pathologies (chronic, acute, neurodegenerative), or motor disorders.

Link: https://labinfind.poliba.it/ricerca-scientifica/pnrr/brief/intocads/

Scientific Publications

Zaccaria G.M., Altini, N., Mongelli, V., Marino, F., Bevilacqua, V. Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma, 2025, p. 105883., doi: 10.1016/j.ijmedinf.2025.105883

Berloco, F., Zaccaria G.M., Altini, N., Colucci, S., Bevilacqua, V. A Multimodal Framework for Assessing the Link between Pathomics, Transcriptomics, and Pancreatic Cancer Mutations. Computerized Medical Imaging and Graphics, 2025, p. 102526. doi: 10.1016/j.compmedimag.2025.102526

Vladimiro Suglia, Cristian Camardella, Gianluca Rinaldi, Domenico Chiaradia, Domenico Buongiorno, Hui Zhou,Antonio Frisoli, Daniele Leonardis, Vitoantonio Bevilacqua. Muscle Network Analysis of a Dynamic Bilateral Task With an Upper Limb Exoskeleton- 19th International Conference on Rehabilitation Robotics (ICORR) May 12–16, 2025, Chicago, USA

Palazzo, L.; Suglia, V.; Grieco, S.; Buongiorno, D.; Brunetti, A.; Carnimeo, L.; Amitrano, F.; Coccia, A.; Pagano, G.; D’Addio, G.; Bevilacqua, V. A Deep Learning-Based Framework Oriented to Pathological Gait Recognition with Inertial Sensors. Sensors 2025, 25, 260. doi: 10.3390/s25010260

Zaccaria G.M., Berloco, F., Buongiorno, D., Brunetti, A., Altini, N., Bevilacqua, V. A time-dependent explainable radiomic analysis from the multi-omic cohort of CPTAC-Pancreatic Ductal Adenocarcinoma. Computer Methods and Programs in Biomedicine, 2024, p.108408. doi: 10.1016/j.cmpb.2024.108408

Zaccaria, G. M., Altini, N., Mezzolla, G., Vegliante, M. C., Stranieri, M., Pappagallo, S. A., Ciavarella, S., Guarini, A., Bevilacqua, V. SurvIAE: Survival prediction with Interpretable Autoencoders from Diffuse Large B-Cells Lymphoma gene expression data. Computer Methods and Programs in Biomedicine, 2024, 244, p.107966. doi: 10.1016/j.cmpb.2023.107966

Berloco, F., Marvulli, P.M., Suglia, V., Colucci, S., Pagano, G., Palazzo, L., Aliani., M., Castellana, G., Guido, P., D’Addio, G., Bevilacqua, V. Enhancing Survival Analysis Model Selection through XAI(t) in Healthcare. Applied Sciences, 2024, 14(14), 6084. doi: 10.3390/app14146084 

Clemente, L., La Rocca, M., Paparella, G., Delussi, M., Tancredi, G., Ricci, K., Procida, G., Introna, A., Brunetti, A., Taurisano, P., Bevilacqua, V., de Tommaso, M. Exploring Aesthetic Perception in Impaired Aging: A Multimodal Brain—Computer Interface Study, 2024, Sensors, 24(7), 2329. doi: 10.3390/s24072329

Sibiliano, E., Buongiorno, D., Lassi, M., Grippo, A., Bessi, V., Sorbi, S., Mazzoni, A., Bevilacqua, V., Brunetti, A.Understanding the Role of Self-Attention in a Transformer Model for the Discrimination of SCD From MCI Using Resting-State EEG, 2024, 28(6):3422-3433. doi:110.1109/JBHI.2024.3390606

Suglia, V., Palazzo, L., Bevilacqua, V., Passantino, A., Pagano, G., D’Addio, G. A Novel Framework Based on Deep Learning Architecture for Continuous Human Activity Recognition with Inertial Sensors. Sensors, 2024, 24, 2199. doi: 10.3390/s24072199

Altini, N., Rossini, M., Turkevi-Nagy, S., Pesce, F., Pontrelli, P., Prencipe, B., Berloco, F., Seshan, S., Gibier, J. B., Dorado, A. P., Bueno, G., Peruzzi, L., Rossi, M., Eccher, A., Li, F., Koumpis, A., Beyan, O., Barratt, J., Huy Quoc, V., Mohan, C., Van Nguyen, H., Cicalese, P. A., Ernst, A., Gesualdo, L., Bevilacqua, V., Becker, J. U. Performance and Limitations of a Supervised Deep Learning Approach for the Histopathological Oxford Classification of Glomeruli with IgA Nephropathy. Computer Methods and Programs in Biomedicine, 2023, p.107814. doi: 10.1016/j.cmpb.2023.107814

Prencipe, B., Delprete, C., Garolla, E., Corallo, F., Gravina, M., Natalicchio, M. I., Buongiorno, D., Bevilacqua, V., Altini, N., Brunetti, A. An Explainable Radiogenomic Framework to Predict Mutational Status of KRAS and EGFR in Lung Adenocarcinoma Patients. Bioengineering. 2023; 10(7):747. doi: 10.3390/bioengineering10070747

Brunetti, A., Buongiorno, D., Altini, N., Bevilacqua, V. Enabling Technologies for Optimized Diagnosis, Therapy and Rehabilitation: Obtained Results and Future Works. In: Bochicchio, M., Siciliano, P., Monteriù, A., Bettelli, A., De Fano, D. (eds) Ambient Assisted Living. ForItAAL 2023. Lecture Notes in Bioengineering. Springer, Cham. doi: 10.1007/978-3-031-63913-5_19

Suglia, V., Brunetti, A., Pasquini, G., Caputo, M., Marvulli, T. M., Sibilano, E., Della Bella, S., Carrozza, P., Beni, C., Naso, D., Monaco, V., Cristella, G., Bevilacqua, V., Buongiorno, D. A Serious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality.Sensors. 2023; 23(11):5017 doi: 10.3390/s23115017

Gentile, E., Brunetti, A., Ricci, K., Vecchio, E., Santoro, C., Sibilano, E., Bevilacqua, V., Iliceto, G., Craighero, L., de Tommaso, M. Effects of movement congruence on motor resonance in early Parkinson’s disease. Scientific Reports, 2023, 13(1), p.14887. doi: 10.1038/s41598-023-42112-2

Sibilano, E., Brunetti, A., Buongiorno, D., Lassi, M., Grippo, A., Bessi, V., Micera, S., Mazzoni, A., Bevilacqua, V. An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG. J Neural Eng. 2023 Feb 6. doi: 10.1088/1741-2552/acb96e

Devices 

---

---

---

---

---