Enrico Longato
Orcid: 0000-0001-5940-645X
According to our database1,
Enrico Longato
authored at least 25 papers
between 2018 and 2024.
Collaborative distances:
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Bibliography
2024
Predicting clinical events characterizing the progression of amyotrophic lateral sclerosis via machine learning approaches using routine visits data: a feasibility study.
BMC Medical Informatics Decis. Mak., December, 2024
Effect of Clinical History on Predictive Model Performance for Renal Complications of Diabetes.
CoRR, 2024
CoRR, 2024
Using Wearable and Environmental Data to Improve the Prediction of Amyotrophic Lateral Sclerosis and Multiple Sclerosis Progression: an Explorative Study.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024), 2024
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2024
Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2024), 2024
2023
iDPP@CLEF 2023 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge.
Dataset, November, 2023
Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review.
Artif. Intell. Medicine, August, 2023
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2023
Baseline Machine Learning Approaches To Predict Multiple Sclerosis Disease Progression.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), 2023
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2023
Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge.
Proceedings of the Working Notes of the Conference and Labs of the Evaluation Forum (CLEF 2023), 2023
Dealing with Data Scarcity in Rare Diseases: Dynamic Bayesian Networks and Transfer Learning to Develop Prognostic Models of Amyotrophic Lateral Sclerosis.
Proceedings of the Artificial Intelligence in Medicine, 2023
2022
Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes.
Comput. Methods Programs Biomed., 2022
Explainable Deep-Learning Model Reveals Past Cardiovascular Disease in Patients with Diabetes Using Free-Form Visit Reports.
Proceedings of the Machine Learning, Optimization, and Data Science, 2022
Baseline Machine Learning Approaches To Predict Amyotrophic Lateral Sclerosis Disease Progression.
Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022
Proceedings of the Experimental IR Meets Multilinguality, Multimodality, and Interaction, 2022
Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge.
Proceedings of the Working Notes of CLEF 2022 - Conference and Labs of the Evaluation Forum, Bologna, Italy, September 5th - to, 2022
2021
A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.
IEEE J. Biomed. Health Informatics, 2021
Comparing the Predictive Power of Heart Failure Hospitalisation Risk Scores in the Diabetic Outpatient Clinic and Primary Care Settings.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021
Recurrent Neural Network to Predict Renal Function Impairment in Diabetic Patients via Longitudinal Routine Check-up Data.
Proceedings of the Artificial Intelligence in Medicine, 2021
2020
A practical perspective on the concordance index for the evaluation and selection of prognostic time-to-event models.
J. Biomed. Informatics, 2020
2019
Detecting Undiagnosed Diabetes: Proof-of-Concept Based on the Health-Information Exchange System of the Veneto Region (North-East Italy).
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data.
Comput. Biol. Medicine, 2018
Importance of Recalibrating Models for Type 2 Diabetes Onset Prediction: Application of the Diabetes Population Risk Tool on the Health and Retirement Study.
Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018