Author

Apiwat Lek-uthai

Chulalongkorn UniversityORCID 0000-0003-2134-8383Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Assay:electronic health records· 2 Approach:deep learning· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Jitkomut SongsiriiD· 2 shared Poomipat BoonyakitanontiD· 2 shared Krisnachai Chomtho· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

3 top collaborators · 3 mutual co-author links

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2 shared papersNeuroscience

Jitkomut SongsiriORCID

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2 papers

Recent·Most cited

NeuroscienceIEEE Transactions on Neural Systems and Rehabilitation EngineeringPeer-reviewedJan 1, 2021

ScoreNet: A Neural network-based post-processing model for identifying epileptic seizure onset and offset in EEGs

Poomipat Boonyakitanont, Apiwat Lek-uthai, Jitkomut Songsiri

ScoreNet improves seizure onset and offset detection in EEGs by using a neural network with a custom loss function, achieving higher F1 scores and lower false positive rates.

20 citations

electronic health recordsdeep learning

𝕏 PostBluesky

NeurosciencebioRxivPreprintJul 15, 2019

A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals

Poomipat Boonyakitanont, Apiwat Lek-uthai, Krisnachai Chomtho, Jitkomut Songsiri

This paper compares ANN and CNN for seizure detection in EEG signals, finding ANN with dominant features achieves higher detection accuracy while CNN has better classification accuracy.

29 citations

electronic health recordsmachine learning (classical)

𝕏 PostBluesky