Active Learning to Understand Infectious Disease Models and Improve Policy Making

PLoS Computational Biology

Volumn 10, Issue 4, 2014, Pages

  Willem, Lander ^a,b   Stijven, Sean ^a,c   Vladislavleva, Ekaterina ^d   Broeckhove, Jan ^a   Beutels, Philippe ^a,e   Hens, Niel ^a,b  

^a UNIVERSITY OF ANTWERP   (Belgium)

^b HASSELT UNIVERSITY   (Belgium)

^c GHENT UNIVERSITY   (Belgium)

^d Evolved Analytics Europe BVBA   (Belgium)

^e UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION MAKING; DISEASES; FUEL ADDITIVES; ITERATIVE METHODS; LEARNING SYSTEMS; VACCINES; VIRUSES;

ACTIVE LEARNING; INFECTIOUS DISEASE; INFECTIOUS DISEASE MODELS; LEARNING APPROACH; MACHINE LEARNING TECHNIQUES; ON-MACHINES; POLICY MAKING; SURROGATE MODELING; SYMBOLIC REGRESSION; SYSTEMATIC EXPLORATION;

COST EFFECTIVENESS;

ACTIVE LEARNING; ARTICLE; COST EFFECTIVENESS ANALYSIS; DISEASE MODEL; EXPERIMENTAL MODEL; HERD IMMUNITY; INFECTION; INFLUENZA VACCINATION; MACHINE LEARNING; SIMULATION; STOCHASTIC MODEL; STUDY DESIGN; VACCINATION; VARICELLA ZOSTER VIRUS; VARICELLA ZOSTER VIRUS VACCINATION; CHICKENPOX; COMMUNICABLE DISEASE; HUMAN; INFLUENZA, HUMAN; LEARNING; MANAGEMENT; STATISTICS; THEORETICAL MODEL;

CHICKENPOX VACCINE; INFLUENZA VACCINE;

CHICKENPOX; CHICKENPOX VACCINE; COMMUNICABLE DISEASES; HUMANS; INFLUENZA VACCINES; INFLUENZA, HUMAN; LEARNING; MODELS, THEORETICAL; POLICY MAKING; STOCHASTIC PROCESSES;

EID: 84901335905     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003563     Document Type: Article

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