Federated learning of predictive models from federated Electronic Health Records
Sign Up to like & getrecommendations! Published in 2018 at "International journal of medical informatics"
DOI: 10.1016/j.ijmedinf.2018.01.007
Abstract: BACKGROUND In an era of "big data," computationally efficient and privacy-aware solutions for large-scale machine learning problems become crucial, especially in the healthcare domain, where large amounts of data are stored in different locations and… read more here.
Keywords: federated learning; electronic health; learning predictive; predictive models ... See more keywords
Machine learning predictive model for severe COVID-19
Sign Up to like & getrecommendations! Published in 2021 at "Infection, Genetics and Evolution"
DOI: 10.1016/j.meegid.2021.104737
Abstract: To develop a modified predictive model for severe COVID-19 in people infected with Sars-Cov-2. We developed the predictive model for severe patients of COVID-19 based on the clinical date from the Tumor Center of Union… read more here.
Keywords: machine learning; predictive model; model; learning predictive ... See more keywords
Emotional stimuli boost incidental learning through predictive processing
Sign Up to like & getrecommendations! Published in 2024 at "Cognition and Emotion"
DOI: 10.1080/02699931.2024.2418444
Abstract: ABSTRACT Extracting regularities and probabilities from the environment is a fundamental and critical ability in an ever-changing surrounding. Previous findings showed that people are highly efficient in learning these regularities and that emotional stimuli are… read more here.
Keywords: learning predictive; stimuli boost; neutral items; incidental learning ... See more keywords
Data augmentation for learning predictive models on EEG: a systematic comparison
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/aca220
Abstract: Objective. The use of deep learning for electroencephalography (EEG) classification tasks has been rapidly growing in the last years, yet its application has been limited by the relatively small size of EEG datasets. Data augmentation,… read more here.
Keywords: predictive models; augmentation learning; data augmentation; models eeg ... See more keywords
Rapid and accurate detection of Shiga toxin-producing Escherichia coli (STEC) serotype O157 : H7 by mass spectrometry directly from the isolate, using 10 potential biomarker peaks and machine learning predictive models.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of medical microbiology"
DOI: 10.1099/jmm.0.001675
Abstract: Introduction. The different pathotypes of Escherichia coli can produce a large number of human diseases. Surveillance is complex since their differentiation is not easy. In particular, the detection of Shiga toxin-producing Escherichia coli (STEC) serotype… read more here.
Keywords: escherichia coli; stec o157; machine learning; learning predictive ... See more keywords
A Systematic Literature Review on Transfer Learning for Predictive Maintenance in Industry 4.0
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3239784
Abstract: The advent of Industry 4.0 has resulted in the widespread usage of novel paradigms and digital technologies within industrial production and manufacturing systems. The objective of making industrial operations monitoring easier also implied the usage… read more here.
Keywords: maintenance; review; transfer learning; predictive maintenance ... See more keywords
Modern Machine-Learning Predictive Models for Diagnosing Infectious Diseases
Sign Up to like & getrecommendations! Published in 2022 at "Computational and Mathematical Methods in Medicine"
DOI: 10.1155/2022/6902321
Abstract: Controlling infectious diseases is a major health priority because they can spread and infect humans, thus evolving into epidemics or pandemics. Therefore, early detection of infectious diseases is a significant need, and many researchers have… read more here.
Keywords: predictive models; infectious diseases; machine learning; modern machine ... See more keywords
Characterization of plasma metabolites and proteins in patients with herpetic neuralgia and development of machine learning predictive models based on metabolomic profiling
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Molecular Neuroscience"
DOI: 10.3389/fnmol.2022.1009677
Abstract: Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus. Postherpetic neuralgia (PHN) is the most common chronic complication of HZ. In this study, we examined the metabolomic… read more here.
Keywords: predictive models; machine learning; characterization plasma; herpetic neuralgia ... See more keywords
Hybrid Deep Learning for Predictive Maintenance: LSTM, GRU, CNN, and Dense Models Applied to Transformer Failure Forecasting
Sign Up to like & getrecommendations! Published in 2025 at "Energies"
DOI: 10.3390/en18215634
Abstract: Data is an important resource for gaining knowledge about the behavior and condition monitoring of machines, enabling the estimation of parameters and the prediction of failures. However, in industrial environments, sensor interruptions often create gaps… read more here.
Keywords: deep learning; learning predictive; dense; lstm ... See more keywords