Results 81 to 90 of about 5,474,085 (350)
Molecular Oncology, EarlyView.Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker +14 more
wiley +1 more source
Random hyperplane search trees in high dimensions
Journal of Computational Geometry, 2015 Given a set S of n ≥ d points in general position in Rd, a random hyperplane split is obtained by sampling d points uniformly at random without replacement from S and splitting based on their affine hull. A random hyperplane search tree is a binary space
Luc Devroye, James King
doaj +1 more source
Molecular Oncology, EarlyView.This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima +6 more
wiley +1 more source
Protected nodes and fringe subtrees in some random trees [PDF]
, 2013 We study protected nodes in various classes of random rooted trees by putting them in the general context of fringe subtrees introduced by Aldous (1991).
L. Devroye, S. Janson
semanticscholar +1 more source
Precision‐Optimised Post‐Stroke Prognoses
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Background Current medicine cannot confidently predict who will recover from post‐stroke impairments. Researchers have sought to bridge this gap by treating the post‐stroke prognostic problem as a machine learning problem, reporting prediction error metrics across samples of patients whose outcomes are known.
Thomas M. H. Hope +4 more
wiley +1 more source
Sharp phase transition for the random-cluster and Potts models via decision trees [PDF]
Annals of Mathematics, 2017 We prove an inequality on decision trees on monotonic measures which generalizes the OSSS inequality on product spaces. As an application, we use this inequality to prove a number of new results on lattice spin models and their random-cluster ...
H. Duminil-Copin +2 more
semanticscholar +1 more source
Extremal properties of random trees [PDF]
Physical Review E, 2001 4 pages ...
Eli Ben-Naim +3 more
openaire +3 more sources
Degree distribution of random Apollonian network structures and Boltzmann sampling [PDF]
Discrete Mathematics & Theoretical Computer Science, 2007 Random Apollonian networks have been recently introduced for representing real graphs. In this paper we study a modified version: random Apollonian network structures (RANS), which preserve the interesting properties of real graphs and can be handled ...
Alexis Darrasse, Michèle Soria
doaj +1 more source
Journal of Computing and Information Technology, 2023 With the advancement of the university information process, more and more application systems are running on the campus network, and the information system becomes larger and more complex. With the rapid growth of network users and the popularization and
Li Yin, Yijun Chen
doaj +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source