Results 121 to 130 of about 68,890 (299)
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
, 2007 . In this paper we consider the possibility of overcoming fragmentation during the construction of decision trees by dividing the values of discriminating nominal attributes into two groups and constructing only two subtrees, one for each group.
K. M. Ho and P. D. Scott +2 more
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Pattern avoidance in binary trees
, 2010 This paper considers the enumeration of trees avoiding a contiguous pattern. We provide an algorithm for computing the generating function that counts n-leaf binary trees avoiding a given binary tree pattern t.
Eric S. Rowland, Rowland, Eric S.
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Advanced Intelligent Discovery, EarlyView.A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi +5 more
wiley +1 more source
Non-Contiguous Pattern Avoidance in Binary Trees
, 2011 We consider the enumeration of binary trees avoiding non-contiguous binary tree patterns. We begin by modifying a known algorithm that counts binary trees avoiding a single contiguous tree pattern.
Wynn, Casey +2 more
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Advanced Intelligent Discovery, EarlyView.Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia +3 more
wiley +1 more source
On Defining Functions on Binary Trees 1
, 2008 Summary. This article is a continuation of an article on defining functions on trees (see [6]). In this article we develop terminology specialized for binary trees, first defining binary trees and binary grammars.
Piotr Rudnicki, Grzegorz Bancerek
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On $n$-equivalence of binary trees.
Notre Dame Journal of Formal Logic, 1987 The paper contains a simple characterization of the binary trees which satisfy the same first-order sentences of quantifier depth n as the binary tree with one root whose branches all have length m (for all n and m). It follows immediately that, e.g., ``finiteness'' is not a first- order property of binary trees. The proof employs the Ehrenfeucht game.
openaire +2 more sources
The Challenge of Handling Structured Missingness in Integrated Data Sources
Advanced Intelligent Discovery, EarlyView.As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson +6 more
wiley +1 more source
Subtree transfer operations and their induced metrics on evolutionary trees [PDF]
, 1999 Leaf-labelled trees are widely used to describe evolutionary relationships, particularly in biology. In this setting, extant species label the leaves of the tree, while the internal vertices correspond to ancestral species. Various techniques exist for
Steel, Mike, Allen, Benjamin Lang
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