ArticleIEEE open journal of engineering in medicine and biology2022
SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification.
Article in IEEE open journal of engineering in medicine and biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- State-Dependent CNN-GRU Reinforcement Framework for Robust EEG-Based Sleep Stage Classification.Biomimetics (Basel, Switzerland) · 2026Article
- Ensemble Fusion Models Using Various Strategies and Machine Learning for EEG Classification.Bioengineering (Basel, Switzerland) · 2024Article
- Gastric Section Correlation Network for Gastric Precancerous Lesion Diagnosis.IEEE open journal of engineering in medicine and biology · 2024Article
- Attention model of EEG signals based on reinforcement learning.Frontiers in human neuroscience · 2024Article
- Performance comparison of bio-inspired and learning-based clustering analysis with machine learning techniques for classification of EEG signals.Frontiers in artificial intelligence · 2023Article
- IoT-Based Reinforcement Learning Using Probabilistic Model for Determining Extensive Exploration through Computational Intelligence for Next-Generation Techniques.Computational intelligence and neuroscience · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The most vital information about the electrical activities of the brain can be obtained with the help of Electroencephalography (EEG) signals. It is quite a powerful tool to analyze the neural activities of the brain and various neurological disorders like epilepsy, schizophrenia, sleep related disorders, parkinson disease etc. can be investigated well with the help of EEG signals.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.