Search Results for author:
Found 7 papers, 1 papers with code
A cost-based multi-layer network approach for the discovery of patient phenotypes
Clinical records frequently include assessments of the characteristics of patients, which may include the completion of various questionnaires.
Probabilistic Active Learning for Active Class Selection
In machine learning, active class selection (ACS) algorithms aim to actively select a class and ask the oracle to provide an instance for that class to optimize a classifier's performance while minimizing the number of requests.
A Framework for Authorial Clustering of Shorter Texts in Latent Semantic Spaces
Authorial clusters are identified thereafter in two scenarios: (a) fully unsupervised and (b) semi-supervised where a small number of shorter texts are known to belong to the same author (must-link constraints) or not (cannot-link constraints).
Cardiac Cohort Classification based on Morphologic and Hemodynamic Parameters extracted from 4D PC-MRI Data
In this work, we investigate the potential of morphological and hemodynamic characteristics, extracted from measured blood flow data in the aorta, for the classification of heart-healthy volunteers and patients with bicuspid aortic valve (BAV).
Incremental Active Opinion Learning Over a Stream of Opinionated Documents
In the experiments, we evaluate the classifier performance over time by varying: (a) the class distribution of the opinionated stream, while assuming that the set of the words in the vocabulary is fixed but their polarities may change with the class distribution; and (b) the number of unknown words arriving at each moment, while the class polarity may also change.
