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Algorithm theory – SWAT 2008 11th Scandinavian Workshop on Algorithm Theory, Gothenburg, Sweden, July 2-4, 2008 : proceedings /
Algorithm Theory-SWAT 2006 10th Scandinavian Workshop on Algorithm Theory, Riga, Latvia, July 6-8, 2006, proceedings /

Design and Analysis of Algorithms first Mediterranean Conference on Algorithms, MedAlg 2012, Kibbutz Ein Gedi, Israel, December 3-5, 2012, proceedings /
Algorithms and architectures for parallel processing 12th International Conference, ICA3PP 2012, Fukuoka, Japan, September 4-7, 2012, proceedings, part I /

Approximation algorithms for complex systems proceedings of the 6th International conference on algorithms for approximation, Ambleside, UK, 31st August - 4th September 2009 /
A kernel-based dose calculation algorithm for kV photon beams with explicit handling of energy and material dependencies

Comparison of Two Highly Automated ECG Algorithms for Detection of Drug‐Induced Cardiac Ion Channel Block
A simple empirical algorithm for optimising depletion power and resolution for dye and system specific STED imaging

Qualitative comparison of choroidal vascularity measurement algorithms
Computational Algorithms that Effectively Reduce Report Defects in Surgical Pathology

A hierarchical evolutionary algorithm for multiobjective optimization in IMRT
The use of a multiobjective evolutionary algorithm to increase flexibility in the search for better IMRT plans

Modern technologies and algorithms for scaffolding assembled genomes
Atlas of diabetes

Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm
Rapid, precise, and reliable measurement of delay discounting using a Bayesian learning algorithm

Algebraic reconstruction of 3D spatial EPR images from high numbers of noisy projections: An improved image reconstruction technique for high resolution fast scan EPR imaging
Supervised classification enables rapid annotation of cell atlases

Cuffless Blood Pressure Monitoring: Promises and Challenges
Comparing demographic and health characteristics of new and existing SNAP recipients: application of a machine learning algorithm

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