Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning
NM Ralbovsky, IK Lednev - Chemical Society Reviews, 2020 - pubs.rsc.org
Many problems exist within the myriad of currently employed screening and diagnostic
methods. Further, an incredibly wide variety of procedures are used to identify an even …
methods. Further, an incredibly wide variety of procedures are used to identify an even …
Natural language processing for requirements engineering: A systematic mapping study
Natural Language Processing for Requirements Engineering (NLP4RE) is an area of
research and development that seeks to apply natural language processing (NLP) …
research and development that seeks to apply natural language processing (NLP) …
Prospects and challenges of the machine learning and data-driven methods for the predictive analysis of power systems: A review
W Strielkowski, A Vlasov, K Selivanov, K Muraviev… - Energies, 2023 - mdpi.com
The use of machine learning and data-driven methods for predictive analysis of power
systems offers the potential to accurately predict and manage the behavior of these systems …
systems offers the potential to accurately predict and manage the behavior of these systems …
Efficient automated processing of the unstructured documents using artificial intelligence: A systematic literature review and future directions
The unstructured data impacts 95% of the organizations and costs them millions of dollars
annually. If managed well, it can significantly improve business productivity. The traditional …
annually. If managed well, it can significantly improve business productivity. The traditional …
[HTML][HTML] Zero-shot learning for requirements classification: An exploratory study
Context: Requirements engineering (RE) researchers have been experimenting with
machine learning (ML) and deep learning (DL) approaches for a range of RE tasks, such as …
machine learning (ML) and deep learning (DL) approaches for a range of RE tasks, such as …
Detection of Parkinson's disease using automated tunable Q wavelet transform technique with EEG signals
Deep brain simulations play an important role to study physiological and neuronal behavior
during Parkinson's disease (PD). Electroencephalogram (EEG) signals may faithfully …
during Parkinson's disease (PD). Electroencephalogram (EEG) signals may faithfully …
[HTML][HTML] Predicting the number of dusty days around the desert wetlands in southeastern Iran using feature selection and machine learning techniques
In the past decades, some desert wetlands have become critical regions for dust production
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …
in the arid and semi-arid regions of the world. Accurate prediction of the number of dusty …
Prcbert: Prompt learning for requirement classification using bert-based pretrained language models
Software requirement classification is a longstanding and important problem in requirement
engineering. Previous studies have applied various machine learning techniques for this …
engineering. Previous studies have applied various machine learning techniques for this …
Machine learning based misbehaviour detection in VANET using consecutive BSM approach
A Sharma, A Jaekel - IEEE Open Journal of Vehicular …, 2021 - ieeexplore.ieee.org
Vehicular ad-hoc network (VANET) is an emerging technology for vehicle-to-vehicle
communication vital for reducing road accidents and traffic congestion in an Intelligent …
communication vital for reducing road accidents and traffic congestion in an Intelligent …
[HTML][HTML] A machine learning approach for hierarchical classification of software requirements
M Binkhonain, L Zhao - Machine Learning with Applications, 2023 - Elsevier
Context: Classification of software requirements into different categories is a critically
important task in requirements engineering (RE). Developing machine learning (ML) …
important task in requirements engineering (RE). Developing machine learning (ML) …