3,327 results for machine learning
Showing 461–480 · 0.87 seconds · RSS
-
Journal Article Full text
Machine learning model to predict mental health crises from electronic health records
…care decisions is not feasible in practice. Therefore, we developed a machine learning model that uses electronic health records to continuously monitor patients for risk of a mental health crisis over a period of 28 days. The model achieves an area under the receiver operating characteristic curve…
-
Journal Article Full text
Statistical stability indices for LIME: Obtaining reliable explanations for machine learning models
Nowadays we are witnessing a transformation of the business processes towards a more computation driven approach. The ever increasing usage of Machine Learning techniques is the clearest example of such trend. This sort of revolution is often providing advantages, such as an increase in prediction…
-
Journal Article Full text
Machine Learning and Deep Learning Approaches for Brain Disease Diagnosis: Principles and Recent Advances
…more accurate and precise. In this study, we present a review on recent machine learning and deep learning approaches in detecting four brain diseases such as Alzheimer's disease (AD), brain tumor, epilepsy, and Parkinson's disease. 147 recent articles on four brain diseases are reviewed…
-
Journal Article Full text
Network intrusion detection system: A systematic study of machine learning and deep learning approaches
…reducing false alarm rates and in detecting novel intrusions. Recently, machine learning (ML) and deep learning (DL)‐based IDS systems are being deployed as potential solutions to detect intrusions across the network in an efficient manner. This article first clarifies the concept of IDS and then…
-
Journal Article Full text
Informed Machine Learning - A Taxonomy and Survey of Integrating Prior Knowledge into Learning Systems
Despite its great success, machine learning can have its limits when dealing with insufficient training data. A potential solution is the additional integration of prior knowledge into the training process which leads to the notion of informed machine learning. In this paper, we present a…
-
Journal Article
Computational Discovery of Transition-metal Complexes: From High-throughput Screening to Machine Learning
…scarcity in transition-metal chemistry motivate specific developments in machine learning representations, model training, and in computational chemistry. Finally, we will conclude with an outlook of areas of opportunity for the accelerated discovery of transition-metal complexes.
-
Journal Article Full text
Machine learning based solutions for security of Internet of Things (IoT): A survey
-
Journal Article Full text
The myth of generalisability in clinical research and machine learning in health care
An emphasis on overly broad notions of generalisability as it pertains to applications of machine learning in health care can overlook situations in which machine learning might provide clinical utility. We believe that this narrow focus on generalisability should be replaced with wider…
-
Journal Article
A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques
…which focuses on stress detection using wearable sensors and applied machine learning techniques. This paper investigates the stress detection approaches adopted in accordance with the sensory devices such as wearable sensors, Electrocardiogram (ECG), Electroencephalography (EEG), and…
-
Journal Article Full text
An efficient optimization approach for designing machine learning models based on genetic algorithm
Abstract Machine learning (ML) methods have shown powerful performance in different application. Nonetheless, designing ML models remains a challenge and requires further research as most procedures adopt a trial and error strategy. In this study, we present a methodology to optimize the…
-
Journal Article Full text
Supervised Machine Learning Models for Prediction of COVID-19 Infection using Epidemiology Dataset
-
Journal Article
A Framework for Effective Application of Machine Learning to Microbiome-Based Classification Problems
Diagnosing diseases using machine learning (ML) is rapidly being adopted in microbiome studies. However, the estimated performance associated with these models is likely overoptimistic. Moreover, there is a trend toward using black box models without a discussion of the difficulty of interpreting…
-
Journal Article
A Review on Machine Learning Styles in Computer Vision—Techniques and Future Directions
Computer applications have considerably shifted from single data processing to machine learning in recent years due to the accessibility and availability of massive volumes of data obtained through the internet and various sources. Machine learning is automating human assistance by training an…
-
Journal Article Full text
Rapid inverse design of metamaterials based on prescribed mechanical behavior through machine learning
…Here, we report a rapid inverse design methodology, leveraging generative machine learning and desktop additive manufacturing, which enables the creation of nearly all possible uniaxial compressive stress‒strain curve cases while accounting for process-dependent errors from printing. Results show…
-
Journal Article Full text
Machine Learning Band Gaps of Doped-TiO2 Photocatalysts from Structural and Morphological Parameters
Abstract Titanium dioxide (TiO2) photocatalysts in the form of thin films are of great interest due to their tunable optical band gaps, Eg’s, which are promising candidates for applications of visible-light photocatalytic activities. Previous studies have shown that processing conditions, dopant…
-
Journal Article Full text
Exchange-correlation functionals for band gaps of solids: benchmark, reparametrization and machine learning
…for the calculation of band gaps. Finally, we demonstrate how to train machine learning models for accurate band gap prediction, using as input structural and composition data, as well as approximate band gaps obtained from density-functional theory.
-
Journal Article Full text
Machine learning for the prediction of acute kidney injury in patients with sepsis
…study aims to establish and validate predictive models based on novel machine learning (ML) algorithms for AKI in critically ill patients with sepsis. METHODS: Data of patients with sepsis were extracted from the Medical Information Mart for Intensive Care III (MIMIC- III) database. Feature…
-
Journal Article Full text
Early detection of type 2 diabetes mellitus using machine learning-based prediction models
…accurate prediction models that can be continuously updated using machine learning approaches. This study compares machine learning-based prediction models (i.e. Glmnet, RF, XGBoost, LightGBM) to commonly used regression models for prediction of undiagnosed T2DM. The performance in prediction of…
-
Journal Article Full text
A machine learning-based intrusion detection for detecting internet of things network attacks
…important problem in the computer security field. This paper proposes a machine learning-based intrusion detection system (ML-IDS) for detecting IoT network attacks. The primary objective of this research focuses on applying ML-supervised algorithm-based IDS for IoT. In the first stage of this…
Showing at most 50 pages. Narrow your search with filters for more specific results.