Publications

Journal Papers

  1. E. Barkan, C. Porta, S. Rabinovici-Cohen, V. Tibollo, S. Quaglini, M. Rizzo, Artificial Intelligence-Based Prediction of Overall Survival in Metastatic Renal Cell Carcinoma. Frontiers in Oncology 13 (2023). https://doi.org/10.3389/fonc.2023.1021684.
  2. A. Lisowska, Sz. Wilk, M. Peleg, SATO (IDEAS expAnded wiTh BCIO): workflow for designers of patient-centered mobile health behaviour change intervention applications. Journal of Biomedical Informatics 138 (2023), 104276. https://doi.org/10.1016/j.jbi.2022.104276.
  3. M. Peleg, Y. Shahar, S. Quaglini, MobiGuide: Guiding Chronic Patients and their Clinicians Anytime, Anywhere. Communications of the ACM 65 (4) (2022), 74-79. https://dx.doi.org/10.1145/3511596
  4. I. Fraterman, S.L.C. Glaser, S. Wilgenhof, S.K. Medlock, H.A. Mallo, R. Cornet, L.V. van de Poll-Franse, A.H. Boekhout, Exploring supportive care and information needs through a proposed eHealth application among melanoma patients undergoing systemic therapy: a qualitative study, Support Care in Cancer 30 (2022), 1-12. https://doi.org/10.1007/s00520-022-07133-z.
  5. E. Parimbelli, S. Wilk, R. Cornet, P. Sniatala, K. Sniatala, S.L.C. Glaser, I. Fraterman, A.H. Boekhout, M. Ottaviano, M. Peleg, A review of AI and data science support for cancer management, Artificial Intelligence in Medicine 117 (2021), 102111. https://doi.org/10.1016/j.artmed.2021.102111.

Conference Papers

  1. A. Kogan, M. Peleg, S.W. Tu, R. Allon, N. Khaitov, I. Hochberg, A Goal-Oriented Methodology for Treatment of Patients with Multimorbidity – Goal Comorbidities (GoCom) Proof-of-Concept Demonstration, in: M. Michalowski, S.S.R. Abidi, S. Abidi, S. (eds): Artificial Intelligence in Medicine, AIME 2022, LNCS, vol 13263, 2022, Springer, pp. 426-430. https://doi.org/10.1007/978-3-031-09342-5_44.
  2. G. Lanzola, F. Polce, V. Tibollo, S. Quaglini, Sz. Wilk, Designing a Testing Environment for the CAPABLE Telemonitoring and Coaching Platform, in: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), Palermo, Italy, 2022: Proceedings, IEEE, 2022, pp. 1112-1117. https://doi.org/10.1109/MELECON53508.2022.9843001.
  3. C. Strusi, A. Dagliati, D. Pala, C. Larizza, R. Bellazzi, S. Quaglini, Taking a walk avoiding polluted routes: An application to a virtual coach for cancer, in: 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON), 2022, pp. 1107-1111. 
  4. S. Quaglini, L. Sacchi, N. Veggiotti, E. Girani, V. Tibollo, Personalising symptoms reporting in telemonitoring applications for cancer patients, in: Challenges of Trustable AI and Added-Value on Health (Proceeding of MIE 2022), Studies in Health Technology and Informatics, 2022, vol. 294, 900-904. https://doi.org/10.3233/SHTI220621.
  5. A. Lisowska, Sz. Wilk, M. Peleg, From Personalized Timely Notification to Healthy Habit Formation: A Feasibility Study of Reinforcement Learning Approaches on Synthetic Data, in: SMARTERCARE 2021. Workshop Proceedings, CEUR-WS, vol. 360, CEUR, 2021, pp. 7-18. [text]
  6. A. Lisowska, S. Lavy, Sz. Wilk, M. Peleg, Personality and Habit Formation: Is There a Link? in: SMARTERCARE 2021. Workshop Proceedings, CEUR-WS, vol. 360, CEUR, 2021, pp. 42-47. [text]
  7. T.M. Buonocore, E. Parimbelli, L. Sacchi, R. Bellazzi, L. Del Campo, S. Quaglini, Improving Keyword-Based Topic Classification in Cancer Patient Forums with Multilingual Transformers, in:  MEDINFO 2021: One World, One Health – Global Partnership for Digital Innovation, Studies in Health Technology and Informatics, 2022, vol. 290, pp. 597-601. https://doi.org/10.3233/SHTI220147.
  8. N. Veggiotti, L. Sacchi, M. Peleg, Enhancing the IDEAS framework with ontology: designing digital interventions for improving cancer patients’ wellbeing, in: AMIA Annual Symposium Proceedings, AMIA, 2021. [preprint]
  9. A. Lisowska, S. Wilk, M. Peleg, Catching patient’s attention at the right time to help them undergo behavioural change: stress classification experiment from blood volume pulse, in: A. Tucker, P.H. Abreu, J. Cardoso, P.P. Rodrigues, D. Riaño. (Eds.), Artificial Intelligence in Medicine. AIME 2021, Lecture Notes in Computer Science, vol. 12721, Springer, Cham, 2021: pp. 72–82. https://doi.org/10.1007/978-3-030-77211-6_8. [preprint]
  10. E. Parimbelli, M. Gabetta, G. Lanzola, F. Polce, S. Wilk, D. Glasspool, A. Kogan, R. Leizer, V. Gisko, N. Veggiotti, S. Panzarasa, R. de Groot, M. Ottaviano, L. Sacchi, R. Cornet, M. Peleg, S. Quaglini, CAncer Patients Better Life Experience (CAPABLE) first proof-of-concept demonstration, in: A. Tucker, P.H. Abreu, J. Cardoso, P.P. Rodrigues, D. Riaño. (Eds.), Artificial Intelligence in Medicine. AIME 2021, Lecture Notes in Computer Science, vol. 12721, Springer, Cham, 2021: pp. 298–303. https://doi.org/10.1007/978-3-030-77211-6_34. [preprint]
  11. A. Lisowska, S. Wilk, M. Peleg, Is it a good time to survey you? cognitive load classification from blood volume pulse, in: 2021 IEEE 34th International Symposium on Computer-Based Medical Systems (CBMS), IEEE, 2021: pp. 137–141. https://doi.org/10.1109/cbms52027.2021.00061. [preprint]
  12. F. Polce, G. Lanzola, M. Gabetta, E. Parimbelli, S. Wilk, D. Glasspool, R. Leizer, A. Kogan, S. Quaglini, The Case Manager: driving medical reasoning in a distributed environment for home patient monitoring, in: Public Health and Informatics, Studies in Health Technology and Informatics, vol. 281, IOS Press, 2021: pp. 610–614. https://doi.org/10.3233/SHTI210243.

Other Publications

  1. The #CS_AIW Project Cluster (including the CAPABLE project): The #CS_AIW White Paper. [latest version at the FAITH project website]
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