Πλοήγηση ανά Θέμα "random forest"
Αποτελέσματα 1-6 από 6
-
An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data
(2022)Stroke is an acute neurological dysfunction attributed to a focal injury of the central nervous system due to reduced blood flow to the brain. Nowadays, stroke is a global threat associated with premature death and huge ... -
Grapevine wood microbiome analysis identifies key fungal pathogens and potential interactions with the bacterial community implicated in grapevine trunk disease appearance
(2021)Background: Grapevine trunk diseases (GTDs) is a disease complex caused by wood pathogenic fungi belonging to genera like Phaeomoniella, Phaeoacremonium, Fomitiporia, Eutypa and members of the family Botryosphaeriaceae. ... -
Heterogeneous data fusion and selection in high-volume molecular and imaging datasets
(2012)In this work, two disparate datasets, concerning the study of the same physiological type of cutaneous melanoma but derived from different donors, one of image (dermatoscopy) and the other of molecular (trascriptomic ... -
Machine Learning in Meningioma MRI: Past to Present. A Narrative Review
(2022)Meningioma is one of the most frequent primary central nervous system tumors. While magnetic resonance imaging (MRI), is the standard radiologic technique for provisional diagnosis and surveillance of meningioma, it ... -
Multi-parametric MRI lesion heterogeneity biomarkers for breast cancer diagnosis
(2020)Purpose: To identify intra-lesion imaging heterogeneity biomarkers in multi-parametric Magnetic Resonance Imaging (mpMRI) for breast lesion diagnosis. Methods: Dynamic Contrast Enhanced (DCE) and Diffusion Weighted Imaging ... -
Nanoscale slip length prediction with machine learning tools
(2021)This work incorporates machine learning (ML) techniques, such as multivariate regression, the multi-layer perceptron, and random forest to predict the slip length at the nanoscale. Data points are collected both from our ...