8.473 hasil untuk machine learning
Menampilkan 601–620 · 0,84 detik · RSS
-
Artikel Jurnal Teks lengkap
AimSeg: A machine-learning-aided tool for axon, inner tongue and myelin segmentation
…analysis tool for axon, inner tongue and myelin segmentation. Aided by machine learning classifiers trained on transmission EM (TEM) images of tissue undergoing remyelination, AimSeg can be used either as an automated workflow or as a user-assisted segmentation tool. Validation results on TEM data…
-
Artikel Jurnal Teks lengkap
Unsupervised machine learning framework for discriminating major variants of concern during COVID-19
…major impact to travel, productivity, and the world economy. Unsupervised machine learning methods have the ability to compress, characterize, and visualize unlabelled data. This paper presents a framework that utilizes unsupervised machine learning methods to discriminate and visualize the…
-
Artikel Jurnal Teks lengkap
Predictive modeling of tax compliance risks: A comparative study of machine learning approaches
Modern enterprises grapple with complex financial data and multidimensional risk interdependencies in their operations. Machine learning offers transformative potential for tax risk assessment and smart auditing solutions. This research analyzes 3,232 tax records from regional manufacturing and…
-
Artikel Jurnal Teks lengkap
Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm
The healthcare industry is generating a massive volume of data, promising a potential goldmine of information that can be extracted through machine learning (ML) techniques. The Intensive Care Unit (ICU) stands out as a focal point within hospitals and provides a rich source of data for informative…
-
Artikel Jurnal Teks lengkap
Innovative data techniques for centrifugal pump optimization with machine learning and AI model
…a crucial role and directly influences the data transformation phase in machine learning (ML) and deep learning (DL) models. The Dewesoft FFT DAQ system is designed to extract the high-quality data from the CPM based on sensor fusion technology. The data recorded from DAQ system undergoes thorough…
-
Artikel Jurnal Teks lengkap
Development and validation of an interpretable longitudinal preeclampsia risk prediction using machine learning
Preeclampsia is a pregnancy-specific disease characterized by new onset hypertension after 20 weeks of gestation that affects 2–8% of all pregnancies and contributes to up to 26% of maternal deaths. Despite extensive clinical research, current predictive tools fail to identify up to 66% of patients…
-
Artikel Jurnal Teks lengkap
Raising awareness of potential biases in medical machine learning: Experience from a Datathon
Objective: To challenge clinicians and informaticians to learn about potential sources of bias in medical machine learning models through investigation of data and predictions from an open-source severity of illness score. Methods: Over a two-day period (total elapsed time approximately 28 hours)…
-
Artikel Jurnal Teks lengkap
Driven early detection of chronic kidney cancer disease based on machine learning technique
…medical task, has seen a breakthrough alteration by incorporating deep learning (DL) methods, mainly in analyzing histopathological images (HIs). Given manual analysis’s inherent complexity and time-consuming aspect, automatic systems leveraging DL methods provide a promising solution. Automated…
-
Artikel Jurnal Teks lengkap
Prediction and validation of anoikis-related genes in neuropathic pain using machine learning
…Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) machine learning algorithms, six key hub genes were identified: hepatocyte growth factor (HGF), matrix metalloproteinase 13 (MMP13), c-abl oncogene 1, non-receptor tyrosine kinase (ABL1), elastase neutrophil…
-
Artikel Jurnal Teks lengkap
Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma
…taken datasets from multiple platforms and designed a statistical and machine learning-based system to determine platform-independent key genes (KGs) for HCC patients. DEGs were determined from each dataset using limma. Individual combined DEGs (icDEGs) were identified from each platform and then…
-
Artikel Jurnal Teks lengkap
Predictive sustainability in agriculture: Machine learning analysis of active ingredient restrictions and bans
…In this context, the analysis of regulatory lists using advanced machine learning and statistical modeling techniques becomes crucial for identifying the key parameters that influence the restriction and banning of active ingredients. This study aims to provide insights that enhance decision-making…
-
Artikel Jurnal Teks lengkap
Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models
…SOFA and APACHE scores struggle to capture complex clinical interactions. Machine learning (ML) models offer a more accurate alternative for predicting outcomes by analyzing large datasets. However, their application in predicting in-hospital mortality for lymphoma patients remains limited…
-
Artikel Jurnal Teks lengkap
OptiSelect and EnShap: Integrating machine learning and game theory for ischemic stroke prediction
Stroke analysis using game theory and machine learning techniques. The study investigates the use of the Shapley value in predictive ischemic brain stroke analysis. Initially, preference algorithms identify the most important features in various machine learning models, including logistic…
-
Artikel Jurnal Teks lengkap
Real estate valuation with multi-source image fusion and enhanced machine learning pipeline
…are subjective and inaccurate, and previous studies have shown that machine learning (ML) approaches perform better in real estate valuation. These valuation models are based on structured tabular data, and few consider integrating multi-source unstructured data such as images. Most previous…
-
Artikel Jurnal Teks lengkap
Retraction: An analysis of machine learning risk factors and risk parity portfolio optimization
-
Artikel Jurnal Teks lengkap
Evaluation of landslide susceptibility based on SMOTE-Tomek sampling and machine learning algorithm
…in Taiping Township, Zhejiang Province, China, using data balancing, machine learning, and data from 1,325 slope units with nine slope characteristics. The dataset was balanced using the Synthetic Minority Oversampling Technique and the Tomek link undersampling method (SMOTE-Tomek). A comparative…
-
Artikel Jurnal Teks lengkap
Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques
…particularly in developing nations like Bangladesh. This study employs machine learning models, including Linear Regression, Ridge Regression, Lasso Regression, Bayesian Ridge, Decision Tree, Gradient Boosting, XGBoost, and CatBoost, to forecast future trends in under-5 mortality. By leveraging…
-
Artikel Jurnal Teks lengkap
An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior
…of existing prediction models by introducing an optimized machine learning framework. The framework integrates an Improved Hunter-Prey Optimization (IHPO) algorithm, an eXtreme Gradient Boosting (XGBoost) model, and SHapley Additive exPlanations (SHAP) theory to predict and interpret corporate ESG…
-
Artikel Jurnal Teks lengkap
A machine learning based variable selection algorithm for binary classification of perinatal mortality
The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive re-weighted sampling(CARS) and logistic…
-
Artikel Jurnal Teks lengkap
Correction: Radiomics-based machine learning for automated detection of Pneumothorax in CT scans
Menampilkan maksimal 50 halaman. Persempit pencarian dengan filter untuk hasil yang lebih spesifik.