Results 71 to 80 of about 2,741,379 (327)
Molecular Oncology, EarlyView.This article advocates integrating temporal dynamics into cancer research. Rather than relying on static snapshots, researchers should increasingly consider adopting dynamic methods—such as live imaging, temporal omics, and liquid biopsies—to track how tumors evolve over time.
Gautier Follain +3 more
wiley +1 more source
Demand-aware traffic cooperation for self-organizing cognitive small-cell networks
International Journal of Distributed Sensor Networks, 2019 This article investigates the problem of efficient spectrum access for traffic demands of self-organizing cognitive small-cell networks, using the coalitional game approach.
Changhua Yao +3 more
doaj +1 more source
Paraconsistent Foundations for Probabilistic Reasoning, Programming and Concept Formation [PDF]
arXiv, 2020 It is argued that 4-valued paraconsistent truth values (called here "p-bits") can serve as a conceptual, mathematical and practical foundation for highly AI-relevant forms of probabilistic logic and probabilistic programming and concept formation. First it is shown that appropriate averaging-across-situations and renormalization of 4-valued p-bits ...
arxiv
A probabilistic distributed algorithm for set intersection and its analysis [PDF]
Theoretical Computer Science, 1987 AbstractA probabilistic algorithm for checking set disjointness and performing set intersection of two sets stored in different machines is presented. The algorithm is intended to minimize the amount of communication between the machines. If n is the total number of elements and k is the number of bits required to represent each of the element, then it
Udi Manber, Thomas G. Kurtz
openaire +2 more sources
Molecular Oncology, EarlyView.This study develops a semi‐supervised classifier integrating multi‐genomic data (1404 training/5893 validation samples) to improve homologous recombination deficiency (HRD) detection in breast cancer. Our method demonstrates prognostic value and predicts chemotherapy/PARP inhibitor sensitivity in HRD+ tumours.
Rong Zhu +12 more
wiley +1 more source
A Theory of Probabilistic Boosting, Decision Trees and Matryoshki [PDF]
arXiv, 2006 We present a theory of boosting probabilistic classifiers. We place ourselves in the situation of a user who only provides a stopping parameter and a probabilistic weak learner/classifier and compare three types of boosting algorithms: probabilistic Adaboost, decision tree, and tree of trees of ... of trees, which we call matryoshka.
arxiv
The efficiency of an algorithm of integer programming: a probabilistic analysis [PDF]
Proceedings of the American Mathematical Society, 1980 A simple algorithm for solving the knapsack problem is shown to lead to examining, on the average, around e 2 n {e^{2\sqrt n }} vectors out of 2 n {2^n} .
openaire +1 more source
FEBS Open Bio, EarlyView.This review highlights how foundation models enhance predictive healthcare by integrating advanced digital twin modeling with multiomics and biomedical data. This approach supports disease management, risk assessment, and personalized medicine, with the goal of optimizing health outcomes through adaptive, interpretable digital simulations, accessible ...
Sakhaa Alsaedi +2 more
wiley +1 more source
A Modified Orthogonal Matching Pursuit for Construction of Sparse Probabilistic Boolean Networks [PDF]
arXiv, 2020 Probabilistic Boolean Networks play a remarkable role in the modelling and control of gene regulatory networks. In this paper, we consider the inverse problem of constructing a sparse probabilistic Boolean network from the prescribed transition probability matrix. We propose a modified orthogonal matching pursuit for solving the inverse problem.
arxiv
A probabilistic reduced basis method for parameter-dependent problems [PDF]
arXiv, 2023 Probabilistic variants of Model Order Reduction (MOR) methods have recently emerged for improving stability and computational performance of classical approaches. In this paper, we propose a probabilistic Reduced Basis Method (RBM) for the approximation of a family of parameter-dependent functions.
arxiv