97 citations · 373 across the 17 of their papers we have counts for
18 papers
Alzheimer's Disease Diagnosis using a Multimodal Approach with 3D MRI and PET
Loukas Ilias, Anthi-Maria Vozinaki, Christos Ntanos +1
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder and a leading cause of death worldwide. Early diagnosis plays an important part especially at the Mild Cognit…
Multi-View Speech Representation Learning for Parkinson's Disease Detection Using Context-guided Cross-modal Attention
George Theodosiou, Loukas Ilias, Dimitris Askounis
Parkinson's disease (PD) is a progressive neurodegenerative disorder that frequently causes speech impairments associated with hypokinetic dysarthria. As speech production relies o…
A Multimodal Framework for Dementia Detection via Linguistic and Acoustic Representation Learning
Loukas Ilias, Dimitris Askounis
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, affecting memory, reasoning, communication, and daily functioning. Early dia…
Recognition of Dysarthria in Amyotrophic Lateral Sclerosis patients using Hypernetworks
Loukas Ilias, Dimitris Askounis
Amyotrophic Lateral Sclerosis (ALS) constitutes a progressive neurodegenerative disease with varying symptoms, including decline in speech intelligibility. Existing studies, which…
Mixture of Experts for Recognizing Depression from Interview and Reading Tasks
Loukas Ilias, Dimitris Askounis
Depression is a mental disorder and can cause a variety of symptoms, including psychological, physical, and social. Speech has been proved an objective marker for the early recogni…
Convolutional Neural Networks and Mixture of Experts for Intrusion Detection in 5G Networks and beyond
Loukas Ilias, George Doukas, Vangelis Lamprou +2
The advent of 6G/NextG networks comes along with a series of benefits, including extreme capacity, reliability, and efficiency. However, these networks may become vulnerable to new…
A Graph Neural Architecture Search Approach for Identifying Bots in Social Media
Georgios Tzoumanekas, Michail Chatzianastasis, Loukas Ilias +3
Social media platforms, including X, Facebook, and Instagram, host millions of daily users, giving rise to bots-automated programs disseminating misinformation and ideologies with…
Depression detection in social media posts using transformer-based models and auxiliary features
Marios Kerasiotis, Loukas Ilias, Dimitris Askounis
The detection of depression in social media posts is crucial due to the increasing prevalence of mental health issues. Traditional machine learning algorithms often fail to capture…
Multimodal Detection of Bots on X (Twitter) using Transformers
Loukas Ilias, Ioannis Michail Kazelidis, Dimitris Askounis
Although not all bots are malicious, the vast majority of them are responsible for spreading misinformation and manipulating the public opinion about several issues, i.e., election…
Multitask learning for recognizing stress and depression in social media
Loukas Ilias, Dimitris Askounis
Stress and depression are prevalent nowadays across people of all ages due to the quick paces of life. People use social media to express their feelings. Thus, social media constit…
Calibration of Transformer-based Models for Identifying Stress and Depression in Social Media
Loukas Ilias, Spiros Mouzakitis, Dimitris Askounis
In today's fast-paced world, the rates of stress and depression present a surge. Social media provide assistance for the early detection of mental health conditions. Existing metho…
Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech
Loukas Ilias, Dimitris Askounis
Alzheimer's disease (AD) constitutes a complex neurocognitive disease and is the main cause of dementia. Although many studies have been proposed targeting at diagnosing dementia t…
Neural Architecture Search with Multimodal Fusion Methods for Diagnosing Dementia
Michail Chatzianastasis, Loukas Ilias, Dimitris Askounis +1
Alzheimer's dementia (AD) affects memory, thinking, and language, deteriorating person's life. An early diagnosis is very important as it enables the person to receive medical help…
A Multimodal Approach for Dementia Detection from Spontaneous Speech with Tensor Fusion Layer
Loukas Ilias, Dimitris Askounis, John Psarras
Alzheimer's disease (AD) is a progressive neurological disorder, meaning that the symptoms develop gradually throughout the years. It is also the main cause of dementia, which affe…
Comparison of Missing Data Imputation Methods using the Framingham Heart study dataset
Konstantinos Psychogyios, Loukas Ilias, Dimitris Askounis
Cardiovascular disease (CVD) is a class of diseases that involve the heart or blood vessels and according to World Health Organization is the leading cause of death worldwide. EHR…
Explainable Verbal Deception Detection using Transformers
Loukas Ilias, Felix Soldner, Bennett Kleinberg
People are regularly confronted with potentially deceptive statements (e.g., fake news, misleading product reviews, or lies about activities). Only few works on automated text-base…
Detecting Dementia from Speech and Transcripts using Transformers
Loukas Ilias, Dimitris Askounis, John Psarras
Alzheimer's disease (AD) constitutes a neurodegenerative disease with serious consequences to peoples' everyday lives, if it is not diagnosed early since there is no available cure…
Explainable Identification of Dementia from Transcripts using Transformer Networks
Loukas Ilias, Dimitris Askounis
Alzheimer's disease (AD) is the main cause of dementia which is accompanied by loss of memory and may lead to severe consequences in peoples' everyday life if not diagnosed on time…