Results 101 to 110 of about 28,744 (310)

Oriented Feature Selection SVM Applied to Cancer Prediction in Precision Medicine

open access: yesIEEE Access, 2018
Advances in the gene sequencing technology and the outbreak of artificial intelligence have made precision medicine a reality recently. Applying machine learning algorithms to cancer prediction using gene expression data helps to discover the link ...
Yang Shen   +4 more
doaj   +1 more source

Regularized Ordinal Regression and the ordinalNet R Package

open access: yes, 2017
Regularization techniques such as the lasso (Tibshirani 1996) and elastic net (Zou and Hastie 2005) can be used to improve regression model coefficient estimation and prediction accuracy, as well as to perform variable selection.
Hanlon, Bret M.   +2 more
core  

Local-Aggregate Modeling for Big-Data via Distributed Optimization: Applications to Neuroimaging [PDF]

open access: yes, 2015
Technological advances have led to a proliferation of structured big data that have matrix-valued covariates. We are specifically motivated to build predictive models for multi-subject neuroimaging data based on each subject's brain imaging scans.
Allen, Genevera I., Hu, Yue
core  

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

open access: yesAdvanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal   +6 more
wiley   +1 more source

Screening Rules for Convex Problems [PDF]

open access: yes, 2016
We propose a new framework for deriving screening rules for convex optimization problems. Our approach covers a large class of constrained and penalized optimization formulations, and works in two steps.
Gärtner, Bernd   +4 more
core   +1 more source

Multimodal Image Guidance in Subthalamic Deep Brain Stimulation for Parkinson's Disease

open access: yesAnnals of Neurology, EarlyView.
Objective Accurate electrode placement and individual stimulation parameters influence the outcomes of subthalamic deep brain stimulation in Parkinson's disease. Neuroimaging‐based models can help evaluate how electrode placement impacts improvement, aiming to reduce the burden of programming.
Patricia Zvarova   +27 more
wiley   +1 more source

Rational Polynomial Coefficient Estimation via Adaptive Sparse PCA-Based Method

open access: yesRemote Sensing
The Rational Function Model (RFM) is composed of numerous highly correlated Rational Polynomial Coefficients (RPCs), establishing a mathematical relationship between two-dimensional images and three-dimensional spatial coordinates.
Tianyu Yan, Yingqian Wang, Pu Wang
doaj   +1 more source

Localized Lasso for High-Dimensional Regression [PDF]

open access: yes, 2016
We introduce the localized Lasso, which is suited for learning models that are both interpretable and have a high predictive power in problems with high dimensionality $d$ and small sample size $n$.
Iwata, Tomoharu   +4 more
core   +1 more source

Challenges and Opportunities in Multi‐Method Integrated Geophysical Prospection of Buried Building Remains at the Sanctuary of Olympia

open access: yesArchaeological Prospection, EarlyView.
ABSTRACT Ancient Olympia was one of the most important sanctuaries and the venue for the Olympic Games in Greek and Roman times. Its remains are located in the Olympia Terrace (Peloponnese, Greece) at the present‐day confluence of the rivers Alpheios and Kladeos at the base of Mount Kronos.
Sarah Bäumler   +10 more
wiley   +1 more source

Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm [PDF]

open access: green, 2021
Vahid Ebrahimi   +6 more
openalex   +1 more source

Home - About - Disclaimer - Privacy