Results 81 to 90 of about 82,044 (253)

Factors Associated with Fibromyalgia Diagnosis amongst People Meeting Criteria: Results from UK Biobank

open access: yesArthritis Care &Research, Accepted Article.
Objective The diagnosis of fibromyalgia (FM) is challenging due to the absence of definitive biomarkers, numerous overlapping comorbidities and its reliance on patient‐reported symptoms. Discrepancies between diagnostic criteria and clinical practice imply the possibility of diagnostic biases, complicating timely and accurate identification. This study
Sung‐A Kim   +2 more
wiley   +1 more source

Distance approximation using Isolation Forests

open access: yesCoRR, 2019
This work briefly explores the possibility of approximating spatial distance (alternatively, similarity) between data points using the Isolation Forest method envisioned for outlier detection. The logic is similar to that of isolation: the more similar or closer two points are, the more random splits it will take to separate them.
openaire   +2 more sources

Individuals with Multi‐Joint Osteoarthritis Demonstrate Larger Longitudinal Declines in Frailty: Data from the Canadian Longitudinal Study on Aging

open access: yesArthritis Care &Research, Accepted Article.
Objective Test the hypothesis that multi‐joint osteoarthritis would modify the relation between time and frailty progression, where more affected joints would lead to larger declines over 6‐years compared to those without osteoarthritis using data from the Canadian Longitudinal Study on Aging.
Carson Halliwell   +2 more
wiley   +1 more source

Isolation forests: looking beyond tree depth

open access: yesCoRR, 2021
The isolation forest algorithm for outlier detection exploits a simple yet effective observation: if taking some multivariate data and making uniformly random cuts across the feature space recursively, it will take fewer such random cuts for an outlier to be left alone in a given subspace as compared to regular observations.
openaire   +2 more sources

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

open access: yesAdvanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch   +3 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

Hybrid Isolation Forest - Application to Intrusion Detection

open access: yesCoRR, 2017
24 pages, working ...
Marteau, Pierre-François   +2 more
openaire   +3 more sources

Laser‐Induced Graphene from Waste Almond Shells

open access: yesAdvanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova   +9 more
wiley   +1 more source

Outlier Ensemble Based on Isolation Forest: The CBOEA Approach

open access: yesFoundations of Computing and Decision Sciences
Outliers are instances that deviate from the norm. In certain fields, their detection is crucial since they are often indicators of interesting events such as system faults and deliberate human actions.
Chaabouni Ali, Boujelben Mohamed Ayman
doaj   +1 more source

Detecting anomalies using rotated isolation forest

open access: yesData Mining and Knowledge Discovery
The Isolation Forest (iForest), proposed by Liu, Ting, and Zhou at TKDE 2012, has become a prominent tool for unsupervised anomaly detection. However, recent research by Hariri, Kind, and Brunner, published in TKDE 2021, has revealed issues with iForest.
Vahideh Monemizadeh, Kourosh Kiani
openaire   +2 more sources

Home - About - Disclaimer - Privacy