8,473 results for machine learning
Showing 21–40 · 0.03 seconds · RSS
-
Journal Article Full text
MLpronto: A tool for democratizing machine learning
The democratization of machine learning is a popular and growing movement. In a world with a wealth of publicly available data, it is important that algorithms for analysis of data are accessible and usable by everyone. We present MLpronto, a system for machine learning analysis that is designed to…
-
Journal Article Full text
Prediction of biological age using machine learning
…of study. This research utilizes health examination data to propose a machine learning-based biological age prediction model that quantifies physiological age through residual life estimation. The model leverages LightGBM, which shows an 11.40% improvement in predictive performance (R-squared)…
-
Journal Article Full text
Machine learning in dentistry: a scoping review
Artificial intelligence (AI), specifically machine learning (ML), is increasingly applied in decision-making for dental diagnosis, prognosis, and treatment. However, the methodological completeness of published models has not been rigorously assessed. We performed a scoping review of PubMed-indexed…
-
Journal Article Full text
Predicting freeway incident duration using machine learning
Accurate prediction of freeway incident duration is important for traffic management and emergency resource allocation. This study evaluates 32 machine-learning model configurations using 828 incident records from the G2504 Hangzhou Ring Freeway in China. Four fixed feature sets containing the top…
-
Journal Article Full text
Research on learning achievement classification based on machine learning
Academic achievement is an important index to measure the quality of education and students’ learning outcomes. Reasonable and accurate prediction of academic achievement can help improve teachers’ educational methods. And it also provides corresponding data support for the formulation of education…
-
Journal Article Full text
Fall Classification by Machine Learning Using Mobile Phones
…to provide data for comparison with the simulated falls. We applied five machine learning classifiers to a large time-series feature set to detect falls. Support vector machines and regularized logistic regression were able to identify a fall with 98% accuracy and classify the type of fall with 99%…
-
Journal Article Full text
Machine Learning Estimates of Natural Product Conformational Energies
Machine learning has been used for estimation of potential energy surfaces to speed up molecular dynamics simulations of small systems. We demonstrate that this approach is feasible for significantly larger, structurally complex molecules, taking the natural product Archazolid A, a potent inhibitor…
-
Journal Article Full text
Machine Learning Methods for Prediction of CDK-Inhibitors
…similarity search methods. In this work we have evaluated and developed machine learning methods for identification of CDKIs. We used different compositional features and evolutionary information in the form of PSSMs, from CDKIs and non-CDKIs for generating SVM and ANN classifiers. In the first…
-
Journal Article Full text
Predictive pollen-based biome modeling using machine learning
This paper investigates suitability of supervised machine learning classification methods for classification of biomes using pollen datasets. We assign modern pollen samples from Africa and Arabia to five biome classes using a previously published African pollen dataset and a global ecosystem…
-
Journal Article Full text
Machine Learning for Characterization of Insect Vector Feeding
…insects and their food source via an electrical circuit, computers, using machine learning algorithms, can learn to recognize insect feeding patterns involved in pathogen transmission. In addition, these machine learning algorithms can show us novel patterns of insect feeding and uncover mechanisms…
-
Journal Article Full text
Machine learning in population health: Opportunities and threats
Abraham D. Flaxman and Theo Vos of the Institute for Health Metrics and Evaluation, University of Washington, discuss near-term applications for ML in population health and name their priorities for ongoing ML development.
-
Journal Article Full text
Forecasting outbound student mobility: A machine learning approach
Background: A country’s ability to become a prominent knowledge economy is tied closely to its ability to acquire skilled people who can compete internationally while resolving challenges of the future. To equip students with competence that can only by gained by being immersed in a foreign…
-
Journal Article Full text
Prediction of hepatitis E using machine learning models
…Methods: Autoregressive integrated moving average(ARIMA), support vector machine(SVM) and long short-term memory(LSTM) recurrent neural network were adopted and compared. ARIMA was implemented by python with the help of statsmodels. SVM was accomplished by matlab with libSVM library. LSTM was…
-
Journal Article Full text
Designing combination therapies with modeling chaperoned machine learning
…was then subjected to a systematic analysis with an ensemble of diverse machine learning methods. Though each method is characterized by a different algorithm, they collectively identified several molecular players that can sensitize tumor cells to cisplatin-induced apoptosis (sensitizers). The…
-
Journal Article Full text
Review of machine learning methods in soft robotics
…limitations, recent studies have applied various approaches based on machine learning. This paper presents existing machine learning techniques in the soft robotic fields and categorizes the implementation of machine learning approaches in different soft robotic applications, which include soft…
-
Journal Article Full text
Predictors of tooth loss: A machine learning approach
…individual’s quality of life. The goal of this study is to develop a machine-learning algorithm to predict complete and incremental tooth loss among adults and to compare the predictive performance of these models. Methods: We used data from the National Health and Nutrition Examination Survey from…
-
Journal Article Full text
Machine learning based approach to exam cheating detection
…approach to detecting potential cases of cheating on the final exam using machine learning techniques. We treat the issue of identifying the potential cases of cheating as an outlier detection problem. We use students’ continuous assessment results to identify abnormal scores on the final exam…
-
Journal Article Full text
Detection of child depression using machine learning methods
…severe consequences in the future. There has been no research employing machine learning (ML) approaches for depression detection among children and adolescents aged 4–17 years in a precisely constructed high prediction dataset, such as Young Minds Matter (YMM). As a result, our objective is to 1)…
-
Journal Article Full text
Expert-enhanced machine learning for cardiac arrhythmia classification
…of them can distinguish between these two. We discuss reasons why deep learning may not yield satisfactory results for this task. We generate new and clinically interpretable features using mathematical optimization for subsequent use within a machine learning (ML) model. These features are…
-
Journal Article Full text
Interpreting tree ensemble machine learning models with endoR
Tree ensemble machine learning models are increasingly used in microbiome science as they are compatible with the compositional, high-dimensional, and sparse structure of sequence-based microbiome data. While such models are often good at predicting phenotypes based on microbiome data, they only…
Showing at most 50 pages. Narrow your search with filters for more specific results.