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Evaluation of Predictive Reliability to Foster Trust in Artificial
  Intelligence. A case study in Multiple Sclerosis

Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis

27 February 2024
Lorenzo Peracchio
G. Nicora
Enea Parimbelli
T. M. Buonocore
Roberto Bergamaschi
Eleonora Tavazzi
A. Dagliati
Riccardo Bellazzi
ArXivPDFHTML

Papers citing "Evaluation of Predictive Reliability to Foster Trust in Artificial Intelligence. A case study in Multiple Sclerosis"

6 / 6 papers shown
Title
FUTURE-AI: International consensus guideline for trustworthy and
  deployable artificial intelligence in healthcare
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir
Aasa Feragen
Abdul Joseph Fofanah
Alejandro F Frangi
Alena Buyx
...
Yi Zeng
Yunusa G Mohammed
Yves Saint James Aquino
Zohaib Salahuddin
M. P. Starmans
AI4TS
59
45
0
11 Aug 2023
Transferring Fairness under Distribution Shifts via Fair Consistency
  Regularization
Transferring Fairness under Distribution Shifts via Fair Consistency Regularization
Bang An
Zora Che
Mucong Ding
Furong Huang
67
31
0
26 Jun 2022
An Overview of Privacy in Machine Learning
An Overview of Privacy in Machine Learning
Emiliano De Cristofaro
SILM
50
83
0
18 May 2020
Secure and Robust Machine Learning for Healthcare: A Survey
Secure and Robust Machine Learning for Healthcare: A Survey
A. Qayyum
Junaid Qadir
Muhammad Bilal
Ala I. Al-Fuqaha
AAML
OOD
70
378
0
21 Jan 2020
Aleatoric and Epistemic Uncertainty with Random Forests
Aleatoric and Epistemic Uncertainty with Random Forests
M. Shaker
Eyke Hüllermeier
BDL
UD
PER
45
71
0
03 Jan 2020
To Trust Or Not To Trust A Classifier
To Trust Or Not To Trust A Classifier
Heinrich Jiang
Been Kim
Melody Y. Guan
Maya R. Gupta
UQCV
127
469
0
30 May 2018
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