Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
The complexity and heterogeneity of schizophrenia symptoms challenge an objective
diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the …
diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the …
Towards artificial intelligence in mental health: a comprehensive survey on the detection of schizophrenia
Abstract Computer Aided Diagnosis systems assist radiologists and doctors in the early
diagnosis of mental disorders such as Alzheimer's, bipolar disorder, depression, autism …
diagnosis of mental disorders such as Alzheimer's, bipolar disorder, depression, autism …
A deep learning-based model for defect detection in laser-powder bed fusion using in-situ thermographic monitoring
H Baumgartl, J Tomas, R Buettner, M Merkel - Progress in Additive …, 2020 - Springer
Additive manufacturing of metal components with laser-powder bed fusion is a very complex
process, since powder has to be melted and cooled in each layer to produce a part. Many …
process, since powder has to be melted and cooled in each layer to produce a part. Many …
Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals
Schizophrenia (SZ) is a severe disorder of the human brain which disturbs behavioral
characteristics such as interruption in thinking, memory, perception, speech and other living …
characteristics such as interruption in thinking, memory, perception, speech and other living …
[HTML][HTML] Schizophrenia classification using machine learning on resting state EEG signal
JR De Miras, AJ Ibáñez-Molina, MF Soriano… - … Signal Processing and …, 2023 - Elsevier
Schizophrenia is a severe mental disorder associated with a wide spectrum of cognitive and
neurophysiological dysfunctions. Early diagnosis is still difficult and based on the …
neurophysiological dysfunctions. Early diagnosis is still difficult and based on the …
Detection of schizophrenia using hybrid of deep learning and brain effective connectivity image from electroencephalogram signal
Detection of mental disorders such as schizophrenia (SZ) through investigating brain
activities recorded via Electroencephalogram (EEG) signals is a promising field in …
activities recorded via Electroencephalogram (EEG) signals is a promising field in …
Development of a machine learning based algorithm to accurately detect schizophrenia based on one-minute EEG recordings
R Buettner, D Beil, S Scholtz, A Djemai - 2020 - scholarspace.manoa.hawaii.edu
While diagnosing schizophrenia by physicians based on patients' history and their overall
mental health is inaccurate, we report on promising results using a novel, fast and reliable …
mental health is inaccurate, we report on promising results using a novel, fast and reliable …
[PDF][PDF] Automatic Detection of Schizophrenia by Applying Deep Learning over Spectrogram Images of EEG Signals.
Accepted: 20 March 2020 This study presents a method that aims to automatically diagnose
Schizophrenia (SZ) patients by using EEG recordings. Unlike many literature studies, the …
Schizophrenia (SZ) patients by using EEG recordings. Unlike many literature studies, the …
Efficient machine learning based detection of heart disease
R Buettner, M Schunter - … on E-health networking, application & …, 2019 - ieeexplore.ieee.org
This paper describes a method to detect possible heart disease using the Random Forests
algorithm. Cardiovascular diseases are the number 1 cause of death globally-an estimated …
algorithm. Cardiovascular diseases are the number 1 cause of death globally-an estimated …
Systematic review on machine-learning algorithms used in wearable-based eHealth data analysis
In this digitized world, data has become an integral part in any domain, including healthcare.
The healthcare industry produces a huge amount of digital data, by utilizing information from …
The healthcare industry produces a huge amount of digital data, by utilizing information from …