2 code implementations • 23 Sep 2022 • Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joao P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
For that, we use more than 100, 000 research papers and build up a knowledge network with more than 64, 000 concept nodes.
1 code implementation • 7 Feb 2022 • Francisco Valente
This paper presents an approach proposed for the Science4cast 2021 competition, organized by the Institute of Advanced Research in Artificial Intelligence, whose main goal was to predict the likelihood of future associations between machine learning concepts in a semantic network.
no code implementations • 15 Oct 2021 • Francisco Valente, Jorge Henriques, Simão Paredes, Teresa Rocha, Paulo de Carvalho, João Morais
In order to achieve the mentioned goals, a three-step methodology was developed: several rules were created by dichotomizing risk factors; such rules were trained with a machine learning classifier to predict the acceptance degree of each rule (the probability that the rule is correct) for each patient; that information was combined and used to compute the risk of mortality and the reliability of such prediction.
no code implementations • 15 Jul 2021 • Francisco Valente, Simão Paredes, Jorge Henriques
In this study, we present a novel clinical decision support system and discuss its interpretability-related properties.
no code implementations • 15 Jun 2021 • Francisco Valente, Jorge Henriques, Simão Paredes, Teresa Rocha, Paulo de Carvalho, João Morais
Some procedures consider a simplification of ETs, using heuristic approaches to select an optimal reduced set of decision rules.