8.473 hasil untuk machine learning
Menampilkan 161–180 · 1,19 detik · RSS
-
Artikel Jurnal Teks lengkap
Against the grain: Leveraging machine learning to analyze mudbrick structures
Mudbricks have been a fundamental building material since the Neolithic, yet their compositional variability and technological flexibility can be challenging for systematic and reproducible fabric characterization. Morphometric parameters such as grain size and shape influence the physical…
-
Artikel Jurnal Teks lengkap
Machine learning-based predictive model for prevention of metabolic syndrome
Metabolic syndrome (MetS) is a chronic disease caused by obesity, high blood pressure, high blood sugar, and dyslipidemia and may lead to cardiovascular disease or type 2 diabetes. Therefore, the detection and prevention of MetS at an early stage are imperative. Individuals can detect MetS early…
-
Artikel Jurnal Teks lengkap
Enabling interpretable machine learning for biological data with reliability scores
Machine learning tools have proven useful across biological disciplines, allowing researchers to draw conclusions from large datasets, and opening up new opportunities for interpreting complex and heterogeneous biological data. Alongside the rapid growth of machine learning, there have also been…
-
Artikel Jurnal Teks lengkap
Enhancing machine learning-based sentiment analysis through feature extraction techniques
…of sentiment analysis tasks. In order to provide directions for future machine learning and feature extraction research, it is important to analyze and summarize feature extraction techniques methodically from a machine learning standpoint. There are several methods under consideration, including…
-
Artikel Jurnal Teks lengkap
Predicting CRISPR-Cas12a guide efficiency for targeting using machine learning
…adjacent motif (PAM) site. These features helped to train a Random Forest machine learning model to improve the accuracy by at least 15% over existing algorithms to predict guide RNA efficiency for the Cas12a enzyme. Despite the progresses, our report underscores the need for more representative…
-
Artikel Jurnal Teks lengkap
A machine learning approach for computation of cardiovascular intrinsic frequencies
…of the IF method in real-time settings. In this paper, we propose a machine learning (ML)-based methodology for determination of IF parameters from a single carotid waveform. We use a sequentially-reduced Feedforward Neural Network (FNN) model for mapping carotid waveforms to the output parameters…
-
Artikel Jurnal Teks lengkap
Explaining machine-learning models for gamma-ray detection and identification
As more complex predictive models are used for gamma-ray spectral analysis, methods are needed to probe and understand their predictions and behavior. Recent work has begun to bring the latest techniques from the field of Explainable Artificial Intelligence (XAI) into the applications of gamma-ray…
-
Artikel Jurnal Teks lengkap
Scope 3 emissions: Data quality and machine learning prediction accuracy
…composition (which Scope 3 categories are reported) and whether machine-learning models can be used to predict Scope 3 emissions for non-reporting firms. We find considerable divergence in the aggregated Scope 3 emissions values from three of the largest data providers (Bloomberg, Refinitiv Eikon…
-
Artikel Jurnal Teks lengkap
Machine learning-based criminal behavior analysis for enhanced digital forensics
…intent. This research introduces an innovative approach that leverages machine learning to analyze internet activity—specifically browser artifacts—shedding new light on criminal behaviors that would otherwise remain hidden.Using advanced machine learning techniques such as Long Short-Term Memory…
-
Artikel Jurnal Teks lengkap
Sustainable visions: unsupervised machine learning insights on global development goals
…data for over 20 years (2000–2022) from 107 countries using unsupervised machine learning (ML) techniques. Our analysis reveals strong positive and negative correlations between certain SDGs (Sustainable Development Goals). Our findings show that progress toward the SDGs is heavily influenced by…
-
Artikel Jurnal Teks lengkap
What makes clinical machine learning fair? A practical ethics framework
Machine learning (ML) can offer a tremendous contribution to medicine by streamlining decision-making, reducing mistakes, improving clinical accuracy and ensuring better patient outcomes. The prospects of a widespread and rapid integration of machine learning in clinical workflow have attracted…
-
Artikel Jurnal Teks lengkap
Enlightened prognosis: Hepatitis prediction with an explainable machine learning approach
…detection of hepatitis is now possible with the recent adoption of machine learning and deep learning approaches. With this in mind, the study investigates the use of traditional machine learning models, specifically classifiers such as logistic regression, support vector machines (SVM), decision…
-
Artikel Jurnal Teks lengkap
Bioactivity-driven prediction of antibacterial synergy using machine learning models
…and the limited scale of experimentally tested combinations. Existing machine-learning approaches for synergy prediction often rely on permissive cross-validation schemes that allow drug pairs to re-appear across folds, leading to inflated performance metrics. A rigorous evaluation framework and…
-
Artikel Jurnal Teks lengkap
Comparative analysis of machine learning techniques for cardiovascular disease prediction
Background and objectives: Early and accurate prediction of cardiovascular disease (CVD) is fundamental for reducing morbidity and mortality. Machine learning (ML) algorithms provide a data-driven, actionable foundation to strengthen clinical decision-making and enable more precise risk…
-
Artikel Jurnal Teks lengkap
Modeling wind erosion susceptibility of Eastern Iran using machine learning
…activities. This study addresses a critical gap by employing advanced machine learning (ML) techniques to generate high-resolution spatial susceptibility maps for wind erosion in the highly vulnerable eastern and northeastern regions of Iran. We evaluated ten distinct ML models using a…
-
Artikel Jurnal Teks lengkap
Enhancing diabetes risk prediction through focal active learning and machine learning models
To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with machine learning models. Existing machine learning models often suffer from poor performance on imbalanced medical datasets, where minority class…
-
Artikel Jurnal Teks lengkap
Machine Learning of Hierarchical Clustering to Segment 2D and 3D Images
We aim to improve segmentation through the use of machine learning tools during region agglomeration. We propose an active learning approach for performing hierarchical agglomerative segmentation from superpixels. Our method combines multiple features at all scales of the agglomerative process…
-
Artikel Jurnal Teks lengkap
Machine Learning Techniques Accurately Classify Microbial Communities by Bacterial Vaginosis Characteristics
…community in the vagina appears to play a role. We use three different machine-learning techniques to classify microbial communities into BV categories. These three techniques include genetic programming (GP), random forests (RF), and logistic regression (LR). We evaluate the classification…
-
Artikel Jurnal Teks lengkap
Machine Learning for Automatic Prediction of the Quality of Electrophysiological Recordings
…to selection biases. Here, we investigate replacing human decisions by a machine learning approach. We define 16 features, such as spike height and width, select the most informative ones using a wrapper method and train a classifier to reproduce the judgement of one of our expert…
-
Artikel Jurnal Teks lengkap
Machine-Learning Approaches for Classifying Haplogroup from Y Chromosome STR Data
…to a haplogroup is presented here. We show that by applying modern machine-learning algorithms we can infer with high accuracy the proper Y chromosome haplogroup of a sample by scoring a relatively small number of Y-linked short tandem repeats (STRs). Learning is based on a diverse ground-truth…
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.