Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Federico Cabitza

Showing results (21-30 of 91) with videos related to

Pageof 10
Sort By:
Studies in Health Technology and Informatics|April 22, 2018
Minimal Important Difference in Outcome of Disc Degenerative Disease Treatment: The Patients' PerspectiveLinda Greta Dui, Federico Cabitza, Pedro Berjano
JAMA|December 21, 2017
Benefits and Risks of Machine Learning Decision Support Systems-ReplyFederico Cabitza, Raffaele Rasoini, Gian Franco Gensini
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
Computer Methods and Programs in Biomedicine|February 3, 2019
PROs in the wild: Assessing the validity of patient reported outcomes in an electronic registryFederico Cabitza, Linda Greta Dui, Giuseppe Banfi
JAMA|July 21, 2017
Unintended Consequences of Machine Learning in MedicineFederico Cabitza, Raffaele Rasoini, Gian Franco Gensini
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
Computers in Biology and Medicine|April 29, 2014
User-driven prioritization of features for a prospective InterPersonal Health Record: perceptions from the Italian contextFederico Cabitza, Carla Simone, Giorgio De Michelis
Clinical Chemistry and Laboratory Medicine|May 4, 2022
How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory dataAnna Carobene, Frida Milella, Lorenzo Famiglini, et al.
Diagnostics (Basel, Switzerland)|March 6, 2021
Has the Flood Entered the Basement? A Systematic Literature Review about Machine Learning in Laboratory MedicineLuca Ronzio, Federico Cabitza, Alessandro Barbaro, et al.
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 10

Showing results (21-30 of 91) with videos related to

Sort By:
Pageof 10
Studies in Health Technology and Informatics|April 22, 2018
Minimal Important Difference in Outcome of Disc Degenerative Disease Treatment: The Patients' PerspectiveLinda Greta Dui, Federico Cabitza, Pedro Berjano
JAMA|December 21, 2017
Benefits and Risks of Machine Learning Decision Support Systems-ReplyFederico Cabitza, Raffaele Rasoini, Gian Franco Gensini
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
Computer Methods and Programs in Biomedicine|February 3, 2019
PROs in the wild: Assessing the validity of patient reported outcomes in an electronic registryFederico Cabitza, Linda Greta Dui, Giuseppe Banfi
JAMA|July 21, 2017
Unintended Consequences of Machine Learning in MedicineFederico Cabitza, Raffaele Rasoini, Gian Franco Gensini
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
Computers in Biology and Medicine|April 29, 2014
User-driven prioritization of features for a prospective InterPersonal Health Record: perceptions from the Italian contextFederico Cabitza, Carla Simone, Giorgio De Michelis
Clinical Chemistry and Laboratory Medicine|May 4, 2022
How is test laboratory data used and characterised by machine learning models? A systematic review of diagnostic and prognostic models developed for COVID-19 patients using only laboratory dataAnna Carobene, Frida Milella, Lorenzo Famiglini, et al.
Diagnostics (Basel, Switzerland)|March 6, 2021
Has the Flood Entered the Basement? A Systematic Literature Review about Machine Learning in Laboratory MedicineLuca Ronzio, Federico Cabitza, Alessandro Barbaro, et al.
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 10