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Andrea Campagner

Showing results (1-10 of 34) with videos related to

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International Journal of Medical Informatics|June 10, 2021
The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studiesFederico Cabitza, Andrea Campagner
Studies in Health Technology and Informatics|June 24, 2020
Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground TruthAndrea Campagner, Federico Cabitza
Annals of Translational Medicine|May 13, 2020
Bridging the "last mile" gap between AI implementation and operation: "data awareness" that mattersFederico Cabitza, Andrea Campagner, Clara Balsano
Studies in Health Technology and Informatics|June 24, 2020
H-Accuracy, an Alternative Metric to Assess Classification Models in MedicineAndrea Campagner, Luca Sconfienza, Federico Cabitza
Health Information Science and Systems|November 1, 2021
External validation of Machine Learning models for COVID-19 detection based on Complete Blood CountAndrea Campagner, Anna Carobene, Federico Cabitza
Computer Methods and Programs in Biomedicine|June 11, 2022
Decisions are not all equal-Introducing a utility metric based on case-wise raters' perceptionsAndrea Campagner, Federico Sternini, Federico Cabitza
Studies in Health Technology and Informatics|May 25, 2022
A Confidence Interval-Based Method for Classifier Re-CalibrationAndrea Campagner, Lorenzo Famiglini, Federico Cabitza
BMC Medical Informatics and Decision Making|September 12, 2020
As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AIFederico Cabitza, Andrea Campagner, Luca Maria Sconfienza
Health Information Science and Systems|February 15, 2021
Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double readingFederico Cabitza, Andrea Campagner, Luca Maria Sconfienza
Medical & Biological Engineering & Computing|March 30, 2022
A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patientsLorenzo Famiglini, Andrea Campagner, Anna Carobene, et al.
Pageof 4

Showing results (1-10 of 34) with videos related to

Sort By:
Pageof 4
International Journal of Medical Informatics|June 10, 2021
The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studiesFederico Cabitza, Andrea Campagner
Studies in Health Technology and Informatics|June 24, 2020
Introducing New Measures of Inter- and Intra-Rater Agreement to Assess the Reliability of Medical Ground TruthAndrea Campagner, Federico Cabitza
Annals of Translational Medicine|May 13, 2020
Bridging the "last mile" gap between AI implementation and operation: "data awareness" that mattersFederico Cabitza, Andrea Campagner, Clara Balsano
Studies in Health Technology and Informatics|June 24, 2020
H-Accuracy, an Alternative Metric to Assess Classification Models in MedicineAndrea Campagner, Luca Sconfienza, Federico Cabitza
Health Information Science and Systems|November 1, 2021
External validation of Machine Learning models for COVID-19 detection based on Complete Blood CountAndrea Campagner, Anna Carobene, Federico Cabitza
Computer Methods and Programs in Biomedicine|June 11, 2022
Decisions are not all equal-Introducing a utility metric based on case-wise raters' perceptionsAndrea Campagner, Federico Sternini, Federico Cabitza
Studies in Health Technology and Informatics|May 25, 2022
A Confidence Interval-Based Method for Classifier Re-CalibrationAndrea Campagner, Lorenzo Famiglini, Federico Cabitza
BMC Medical Informatics and Decision Making|September 12, 2020
As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AIFederico Cabitza, Andrea Campagner, Luca Maria Sconfienza
Health Information Science and Systems|February 15, 2021
Studying human-AI collaboration protocols: the case of the Kasparov's law in radiological double readingFederico Cabitza, Andrea Campagner, Luca Maria Sconfienza
Medical & Biological Engineering & Computing|March 30, 2022
A robust and parsimonious machine learning method to predict ICU admission of COVID-19 patientsLorenzo Famiglini, Andrea Campagner, Anna Carobene, et al.
Pageof 4