Results 71 to 80 of about 3,227,878 (310)
Prediksi Harga Bitcoin Menggunakan Metode Random Forest
Jurnal Komputer Terapan, 2021 Pada masa pandemic ini, transaksi keuangan virtual mengalami peningkatan tajam. Dikarenakan penyimpanan asset maupun bentuk jual-beli bertransformasi menggunakan layanan digital.
Siti Saadah, Haifa Salsabila
doaj +1 more source
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
IEICE Transactions on Information and Systems, 2015 Machine learning is used in various fields and demand for implementations is increasing. Within machine learning, a Random Forest is a multi-class classifier with high-performance classification, achieved using bagging and feature selection, and is capable of high-speed training and classification. However, as a type of ensemble learning, Random Forest
MISHINA, Yohei +4 more
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Accurate and noninvasive prostate cancer detection using plasma‐derived extracellular vesicle RNA
FEBS Open Bio, EarlyView.Plasma extracellular vesicles were captured with WGA‐conjugated magnetic beads and profiled for RNA biomarkers. A three‐RNA panel (NM_024955, NR_047469, and NR_002564) distinguished prostate cancer from healthy controls and benign prostatic hyperplasia, supporting a simple, noninvasive approach to improve prostate cancer detection.
Hanping Wei, Haoran Wu, Wei Feng
wiley +1 more source
CoRRRandom forest (RF) stands out as a highly favored machine learning approach for classification problems. The effectiveness of RF hinges on two key factors: the accuracy of individual trees and the diversity among them. In this study, we introduce a novel approach called heterogeneous RF (HRF), designed to enhance tree diversity in a meaningful way ...
Ye-eun Kim +2 more
openaire +3 more sources
Journal of Thoracic Oncology, 2011 In the article by Chen et al,1 the authors used Random Survival Forests (RSF) as part of their approach for analyzing the data. In this note, we will explain RSF in a nontechnical way; precise details of the RSF method are described in the article by Ishwaran et al.2 RSF are an adaptation of Random Forests (RF)3 designed to be used for survival data ...
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FEBS Open Bio, EarlyView.Using peripheral blood for determining B‐cell or T‐cell clonality is more reliable when we use cell‐free RNA (cfRNA) because cells release blood significantly more RNA than DNA. Next‐generation sequencing (NGS) of cfRNA allows us to evaluate fragment cfRNA and evaluate clonality reliably without the need for prior determination of the specific dominant
Adam Albitar +11 more
wiley +1 more source
Aging and Cancer, EarlyView.Cancer treatment is associated with measurable acceleration of biological aging across epigenetic, telomere, senescence, and immune biomarkers. However, biomarker validation and interventional strategies remain limited, especially in hematologic malignancies, underscoring the need for standardized multi‐omic aging assessments and adequately powered ...
Moataz Ellithi +3 more
wiley +1 more source
Predicting IPO initial returns using random forest
Borsa Istanbul Review, 2020 Empirical analyses of IPO initial returns are heavily dependent on linear regression models. However, these models can be inefficient due to its sensitivity to outliers which are common in IPO data.
Boubekeur Baba, Güven Sevil
doaj +1 more source
Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi +8 more
wiley +1 more source