Marios Adamou
Biographic Data
| ID | 7645330 |
|---|---|
| NAME | Marios Adamou |
| GIVEN NAMES | Marios |
| FAMILY NAME | Adamou |
| SIGNATURE | ADAMOU M |
| AFFILIATIONS | University of Huddersfield |
| ORCID | 0000-0002-4303-664X |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
De-diagnosis and the problem of revisability in adult ADHD and autism
Recorded diagnoses of attention-deficit/hyperactivity disorder (ADHD) and autism in adults have risen sharply across high-income health systems, and demand for assessment has risen faster still, while the best available population estimates of prevalence appear to have moved comparatively little. This paper treats that divergence as an analytic problem. We argue that adult neurodevelopmental diagnosis has undergone a threefold transformation: it …
Camouflaging in autism as a dual-normative construct
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 …
Integrating explainable AI with clinical features to enhance ADHD diagnostic understanding
Integrating multimodal clinical features with transparent ML methods provides interpretable, clinically aligned insights into adult ADHD diagnosis. The combined SHAP-EDA approach identifies actionable thresholds, clarifies differential feature contributions, and highlights the importance of comorbidity and demographic context in diagnostic evaluation. These findings support a patient-centred, data-driven framework for improving diagnostic consist…
The adult ADHD assessment quality assurance standard
The AQAS has been developed as a practical resource to support reliable and valid diagnostic assessments of adult ADHD. It is intended to complement formal training. A secondary objective is to empower patients by providing them with evidence-based information on what to expect from an assessment and assessment report
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…
No prominent works on this page.
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…
The adult ADHD assessment quality assurance standard
The AQAS has been developed as a practical resource to support reliable and valid diagnostic assessments of adult ADHD. It is intended to complement formal training. A secondary objective is to empower patients by providing them with evidence-based information on what to expect from an assessment and assessment report
Integrating explainable AI with clinical features to enhance ADHD diagnostic understanding
Integrating multimodal clinical features with transparent ML methods provides interpretable, clinically aligned insights into adult ADHD diagnosis. The combined SHAP-EDA approach identifies actionable thresholds, clarifies differential feature contributions, and highlights the importance of comorbidity and demographic context in diagnostic evaluation. These findings support a patient-centred, data-driven framework for improving diagnostic consist…
De-diagnosis and the problem of revisability in adult ADHD and autism
Recorded diagnoses of attention-deficit/hyperactivity disorder (ADHD) and autism in adults have risen sharply across high-income health systems, and demand for assessment has risen faster still, while the best available population estimates of prevalence appear to have moved comparatively little. This paper treats that divergence as an analytic problem. We argue that adult neurodevelopmental diagnosis has undergone a threefold transformation: it …
Camouflaging in autism as a dual-normative construct
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 …
Attention Deficit Hyperactivity Disorder (5 works) · Autism Spectrum Disorder Research (3 works) · Functional Brain Connectivity Studies (3 works) · Computer Science (2 works) · Context (archaeology (2 works) · Empirical research (2 works) · Medicine (2 works) · Psychiatry (2 works) · Psychology (2 works) · adult ADHD (1 work)