Journal Papers

  1. I. Fraterman, B. Wollersheim, V. Tibollo, S. Glaser, S. Medlock, R. Cornet, M. Gabetta, V. Gisko, E. Barkan, N. Di Flora, D. Glasspool, A. Kogan, G. Lanzola, R. Leizer, H. Mallo, M. Ottaviano, M. Peleg, L van de Poll-Franse, N. Veggiotti, K. Śniatała, Sz. Wilk, E. Parimbelli, S. Quaglini, M. Rizzo, L. Locatti, A. Boekhout, L. Sacchi, S. Wilgenhof, An eHealth App (CAPABLE) Providing Symptom Monitoring, Well-Being Interventions, and Educational Material for Patients With Melanoma Treated With Immune Checkpoint Inhibitors: Protocol for an Exploratory Intervention TrialJMIR Research Protocols 12 (2023), e49252. https://doi.org/10.2196/49252.
  2. G. Lanzola, F. Polce, E. Parimbelli, M. Gabetta, R. Cornet, R. DeGroot, A. Kogan, D. Glasspool, Sz. Wilk, S. Quaglini, The Case Manager: An Agent Controlling the Activation of Knowledge Sources in a FHIR-based Distributed Reasoning EnvironmentApplied Clinical Informatics (2023). https://doi.org/10.1055/a-2113-4443.
  3. 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.
  4. 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.
  5. 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
  6. 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.
  7. 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.

Book Chapters

  1. S. Rabinovici-Cohen: Artificial Intelligence to Support Choices in Neoadjuvant Chemotherapy in Breast Cancer Patients, in: Technology in Healthcare: Introduction, Clinical Impacts, Workflow Improvement, Structuring and Assessment, now publishers, 2024, chapter 16. [preprint]

Conference Papers

  1. A. Kogan, S. W. Tu, M. Peleg, Inferring Monitoring Recommendation Frequencies for Multimorbidity Patients, in: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 21-27. [text]
  2. A. Zaitoun, T. Sagi, Sz. Wilk, M. Peleg, Can Large Language Models Augment a Biomedical Ontology with Missing Concepts and Relations? In: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 43-52. [text]
  3. A. Lisowska, Sz. Wilk, M. Peleg, Personalising Digital Health Behaviour Change Interventions using Machine Learning and Domain Knowledge, in: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 53-61. [text]
  4. N. Veggiotti, S. Panzarasa, V. Tibollo, S. Quaglini, G. Lanzola, L. Sacchi, Defining and Simulating Scenarios for the CAPABLE Clinical Decision Support System. in: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 62-74. [text]
  5. L. Sacchi, N. Veggiotti, S. Quaglini: Challenges in Symptoms Reporting in a Patient’s Application. In: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 75-81. [text]
  6. A. Kogan, R. Leizer, Sz. Wilk, D. Glasspool, A Hybrid Execution Environment for Computer-Interpretable Guidelines in PROforma. In: Proceedings of the 13th International Workshop on Knowledge Representation for Health Care (KR4HC), 2023, pp. 82-89. [text]
  7. 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.
  8. 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.
  9. 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. 
  10. 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.
  11. 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]
  12. 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]
  13. 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.
  14. 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]
  15. 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]
  16. 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]
  17. 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]
  18. 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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