Grigoris Antoniou
Biographic Data
| ID | 7906020 |
|---|---|
| NAME | Grigoris Antoniou |
| GIVEN NAMES | Grigoris |
| FAMILY NAME | Antoniou |
| SIGNATURE | ANTONIOU G |
| AFFILIATIONS | Leeds Beckett University |
| ORCID | 0000-0003-3673-6602 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Older people's perceptions of emerging transport technologies and intentions to use them
This study explores how older people perceive emerging transport technologies, designed to reform the future of mobility. With older populations rising dramatically and being on the one hand the age group most vulnerable to social exclusion and on the other hand increasingly influential in societal structures, the transport sector is under pressure to adapt to their diverse and sometimes specialised mobility needs. In this context, the study expl…
A mathematical framework for modelling the dynamic nature of ADHD symptoms
The proposed mathematical models offer a novel, quantitative framework for understanding and representing the dynamic nature of ADHD symptoms. Grounded in neuropsychological theory, these interpretable models provide a potential advance over static descriptions and may facilitate improved clinical assessment, personalized treatment strategies, and targeted research into the mechanisms underlying ADHD. Further empirical validation is warranted to …
Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence
Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting a large percentage of the adult population. A series of ongoing efforts has led to the development of a hybrid AI algorithm (a combination of a machine learning model and a knowledge-based model) for assisting adult ADHD diagnosis, and its clinical trial currently operating in the largest National Health Service (NHS) for adults with ADHD in the UK. Most re…
A Predictive Analysis of Heart Rates Using Machine Learning Techniques
Heart disease, caused by low heart rate, is one of the most significant causes of mortality in the world today. Therefore, it is critical to monitor heart health by identifying the deviation in the heart rate very early, which makes it easier to detect and manage the heart's function irregularities at a very early stage. The fast-growing use of advanced technology such as the Internet of Things (IoT), wearable monitoring systems and artificial in…
No prominent works on this page.
A Predictive Analysis of Heart Rates Using Machine Learning Techniques
Heart disease, caused by low heart rate, is one of the most significant causes of mortality in the world today. Therefore, it is critical to monitor heart health by identifying the deviation in the heart rate very early, which makes it easier to detect and manage the heart's function irregularities at a very early stage. The fast-growing use of advanced technology such as the Internet of Things (IoT), wearable monitoring systems and artificial in…
Diagnosing attention-deficit hyperactivity disorder (ADHD) using artificial intelligence
Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting a large percentage of the adult population. A series of ongoing efforts has led to the development of a hybrid AI algorithm (a combination of a machine learning model and a knowledge-based model) for assisting adult ADHD diagnosis, and its clinical trial currently operating in the largest National Health Service (NHS) for adults with ADHD in the UK. Most re…
Older people's perceptions of emerging transport technologies and intentions to use them
This study explores how older people perceive emerging transport technologies, designed to reform the future of mobility. With older populations rising dramatically and being on the one hand the age group most vulnerable to social exclusion and on the other hand increasingly influential in societal structures, the transport sector is under pressure to adapt to their diverse and sometimes specialised mobility needs. In this context, the study expl…
A mathematical framework for modelling the dynamic nature of ADHD symptoms
The proposed mathematical models offer a novel, quantitative framework for understanding and representing the dynamic nature of ADHD symptoms. Grounded in neuropsychological theory, these interpretable models provide a potential advance over static descriptions and may facilitate improved clinical assessment, personalized treatment strategies, and targeted research into the mechanisms underlying ADHD. Further empirical validation is warranted to …
Artificial Intelligence (2 works) · Attention Deficit Hyperactivity Disorder (2 works) · Computer Science (2 works) · Functional Brain Connectivity Studies (2 works) · Machine learning (2 works) · Accelerometer (1 work) · Artificial Intelligence in Healthcare (1 work) · Artificial neural network (1 work) · Autoregressive integrated moving average (1 work) · Clinical Practice (1 work)