Isotta Trescato – Systems Biology and Bioinformatics Group

February 6, 2024

Guazzo A, Trescato I, Longato E, Tavazzi E, Vettoretti M, Di Camillo B. Baseline Machine Learning Approaches To Predict Multiple Sclerosis Disease Progression. CLEF 2023 Working Notes, CEUR Workshop Proceedings 2023

November 8, 2023January 30, 2024

Trescato I., Roversi C., Vettoretti M., Di Camillo B., Facchinetti A. A model to forecast the two-year variation of subjective wellbeing in the elderly population. BMC Med Inform and Decis Mak 2023

September 11, 2023February 6, 2024

Faggioli G, Guazzo A, Marchesin S, Menotti L, Trescato I, Aidos H, Bergamaschi R, Birolo G, Paola Cavalla P, Chiò A, Dagliati A, de Carvalho M, Di Nunzio G M, Fariselli P, García Dominguez J M, Gromicho M, Longato E, C Madeira S C, Manera U, Silvello G, Tavazzi E, Tavazzi E, Vettoretti M, Di Camillo B, Ferro N. Intelligent Disease Progression Prediction: Overview of iDPP@ CLEF 2023. Lect Notes in Comp Science (LNCS) 2023

September 11, 2023February 6, 2024

Faggioli G, Guazzo A, Marchesin S, Menotti L, Trescato I, Aidos H, Bergamaschi R, Birolo G, Cavalla P, Chiò A, Dagliati A, de Carvalho M, Di Nunzio GM, Fariselli P , García Dominguez LM, Gromicho M, Longato E, Madeira SC, Manera U, Silvello G, Tavazzi E, Tavazzi E, Vettoretti M, Di Camillo B, Ferro N. Overview of iDPP@ CLEF 2023: the intelligent disease progression prediction challenge. In: Int Conf of the Cross-Language Ev Forum for Europ Lan. Cham: Springer Nat Switz, 2023

August 22, 2022

Trescato I, Guazzo A, Longato E, Hazizaj E, Roversi C, Tavazzi E, Vettoretti M, Di Camillo B. Baseline Machine Learning Approaches To Predict Amyotrophic Lateral Sclerosis Disease Progression. In: Faggioli G, Ferro N, Hanbury A, Potthast M (Eds.), CLEF 2022 Working Notes, CEUR Workshop Proceedings (CEUR-WS.org) 2022

November 10, 2021November 11, 2021

Next week we will attend the 17th Computational Intelligence Methods for Bioinformatics and Biostatistics conference (CIBB 2021) with three contributions related to Amyotrophic Lateral Sclerosis heterogeneity and progression, and to wellbeing perception in the elderly population

“Identifying extreme behaviours in Amyotrophic Lateral Sclerosis patients at diagnosis through Archetypal Analysis” (Trescato I, Tavazzi E, Vettoretti M, Vasta S, Chiò A, Di Camillo B).
“Inspecting Progression Trajectories in Amyotrophic Lateral Sclerosis using Process Mining” (Tavazzi E, Gatta R, Vallati M, Cotti Piccinelli S, Filosto M, Castellano M, Di Camillo B).
“Linear regression modelling to assess the impact of socio-economic, demographic and health-related variables on wellbeing in the elderly population” (Trescato I, Roversi C, Vettoretti M, Di Camillo B, Facchinetti A).

For more details, check the conference website: http://www.isa.cnr.it/cibb2021/

You can find us at the IEEE Biomedical Health Informatics conference (BHI 2021) with our contribution “Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores Across Different Care Settings”

We’ll join the IEEE Biomedical Health Informatics conference (BHI 2021) with our contribution entitled “Identification of demographic, socio-economic and health-related factors influencing wellbeing in the elderly population using regression models”

We recently developed a new variable ranking algorithm for machine learning models. Check out our contribution at the IEEE Biomedical Health Informatics conference (BHI 2021): “A New Methodology to Perform Variable Ranking in Machine Learning Models with Correlated Features: In Silico Validation”

It’s a pleasure to join the IEEE Biomedical Health Informatics conference (BHI 2021) with our contribution entitled “Predicting hypertension onset using logistic regression models with labs and/or easily accessible variables: the role of blood pressure measurements” #machinelearning #predictivemodel #hypertension #bhi2021