113,116 results for machine learning
Showing 941–960 · 0.86 seconds · RSS
-
Journal Article Full text
Fully First-Principles Surface Spectroscopy with Machine Learning
…it is possible to model VSFG signals with fully ab initio accuracy using machine learning and illustrate the versatility of our approach on the water/air interface. Our strategy allows us to identify the main sources of theoretical inaccuracy and establish a clear pathway toward the modeling of…
-
Journal Article Full text
Protein pKa prediction by tree-based machine learning
…accurately determine their pKa values. Here, we present four tree-based machine learning models for protein pKa prediction. The four models, Random Forest, Extra Trees, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM), were trained on three experimental PDB and pKa…
-
Journal Article Full text
Machine learning for cross-scale microscopy of viruses
…manner at molecular resolution and is increasingly enhanced by machine learning and deep learning. Here we discuss how state-of-the-art artificial intelligence (AI) augments light and electron microscopy and advances virological research of cells. We describe current procedures for image denoising…
-
Journal Article Full text
Breast Cancer Detection and Prevention Using Machine Learning
…in situ (DCIS). The advancements in artificial intelligence (AI) and machine learning (ML) techniques have made it possible to develop more accurate and reliable models for diagnosing and treating this disease. From the literature, it is evident that the incorporation of MRI and convolutional…
-
Journal Article Full text
Application of statistical machine learning in biomarker selection
In the recent JAVELIN Bladder 100 phase 3 trial, avelumab plus best supportive care significantly prolonged overall survival relative to best supportive care alone as first-line maintenance therapy following first-line platinum-based chemotherapy in patients with advanced urothelial cancer (aUC)…
-
Journal Article Full text
Deciphering RNA splicing logic with interpretable machine learning
Machine learning methods, particularly neural networks trained on large datasets, are transforming how scientists approach scientific discovery and experimental design. However, current state-of-the-art neural networks are limited by their uninterpretability: Despite their excellent accuracy, they…
-
Journal Article Full text
Non-Invasive Blood Pressure Sensing via Machine Learning
In this paper, a machine learning (ML) approach to estimate blood pressure (BP) using photoplethysmography (PPG) is presented. The final aim of this paper was to develop ML methods for estimating blood pressure (BP) in a non-invasive way that is suitable in a telemedicine health-care monitoring…
-
Journal Article Full text
A benchmark dataset for machine learning in ecotoxicology
The use of machine learning for predicting ecotoxicological outcomes is promising, but underutilized. The curation of data with informative features requires both expertise in machine learning as well as a strong biological and ecotoxicological background, which we consider a barrier of entry for…
-
Journal Article Full text
Infection prediction in swine populations with machine learning
…of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention…
-
Journal Article Full text
Automated Detection of Aortic Stenosis using Machine Learning
AIMS: Aortic stenosis (AS) is a degenerative valve condition that is under-diagnosed and undertreated. Detection of AS using limited 2D echocardiography could enable screening and improve appropriate referral and treatment of this condition. We aimed to develop methods for automated detection of AS…
-
Journal Article Full text
Preinterventional Third-Molar Assessment Using Robust Machine Learning
Machine learning (ML) models, especially deep neural networks, are increasingly being used for the analysis of medical images and as a supporting tool for clinical decision-making. In this study, we propose an artificial intelligence system to facilitate dental decision-making for the removal of…
-
Journal Article Full text
Granite classification using machine learning and edge computing
…efficient. Methods: For this purpose,researchers in this work developed a machine learning based granite classifier us-ing Edge Computing and a website to help users in choosing which granite wouldgo well with their d ´ecor is also built. The developed system consists of a colorsensor [TCS3200]…
-
Journal Article Full text
Δ(2) machine learning for reaction property prediction
The emergence of Δ-learning models, whereby machine learning (ML) is used to predict a correction to a low-level energy calculation, provides a versatile route to accelerate high-level energy evaluations at a given geometry. However, Δ-learning models are inapplicable to reaction properties like…
-
Journal Article Full text
Automated machine learning for genome wide association studies
…RESULTS: We develop, apply, and comparatively evaluate an automated machine learning (AutoML) approach, customized for genomic data that delivers reliable predictive and diagnostic models, the set of genetic variants that are important for predictions (called a biosignature), and an estimate of the…
-
Journal Article Full text
Prediction of Parkinson’s Disease Using Machine Learning Methods
…them into risk predictions, which were built using eight commonly used machine learning models to allow for comprehensive assessment. Finally, the Shapley Additive Explanations (SHAP) method was used to investigate the contributions of each factor. We found that models built with demographic…
-
Journal Article Full text
Intermolecular Non-Bonded Interactions from Machine Learning Datasets
…as a continuous force function. In this paper, we employ well-developed machine learning techniques to construct a general purpose intermolecular non-bonded interaction force field for organic polymers. The original ab initio dataset SOFG-31 was calculated by us and has been well documented, and…
-
Journal Article Full text
Retracted: Automation of Cephalometrics Using Machine Learning Methods
Showing at most 50 pages. Narrow your search with filters for more specific results.