Papers Data Mining
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Discovering multiple antibiotic resistance phenotypes using diverse top-k subgroup list discovery
Antibiotic resistance is one of the major global threats to human health and occurs when antibiotics lose their ability to combat bacterial infections. In this problem, a clinical decision support system could use phenot…
Data MiningDecision MakingDiverse Top-k Subgroup List DiscoveryPatient Phenotyping+1Subgroups: A Python library for Subgroup Discovery
This manuscript introduces Subgroups, an openly accessible Python library designed to ease the use of Subgroup Discovery (SD) algorithms for machine learning and data science. The Subgroups Library offers several advanta…
Data MiningSubgroup DiscoveryVLSD—An Efficient Subgroup Discovery Algorithm Based on Equivalence Classes and Optimistic Estimate
Subgroup Discovery (SD) is a supervised data mining technique for identifying a set of relations (subgroups) among attributes from a dataset with respect to a target attribute. Two key components of this technique are (i…
AttributeData MiningSubgroup DiscoveryA methodology based on Trace-based clustering for patient phenotyping
Background: The current situation of critical progression as regards the resistance of bacteria to antibiotics has led to the use of machine learning techniques in order to provide clinicians with new knowledge for deci…
ClusteringData MiningDecision MakingPatient Phenotyping