The Global Goals
In 2015, UN member states agreed to 17 global to end poverty, protect the planet and ensure prosperity for all. Hossein's work contributes towards the following SDG(s):
About Hossein
Welcome to My Profile: Collaboration and Impact in E-Health and AI for Healthcare InnovationÌý
Hossein Ahmadi largely engaged and built relationships with several industrial stakeholders in the region active in the e-health area during my presence in EPIC project including Akumen Ltd (https://akumen.co.uk/), Arts Well UK CIC (https://arts-well.com/), Chromotropic Limited, Ross Raymond-Jones and n-Coders (https://www.n-coders.co.uk/). In the EPIC project, Hossein supported the mentioned SMEs Activities in AI and Machine Learning within the context of UK. He was the main lead to provide 12-hours support to those SMEs. Now, he has joined various projects, i.e., AI and dental service provision rapid evidence assessment, use of machine learning and data analytics techniques to recognize and correct anticholinergic inducing polypharmacy in older people with intellectual disabilities and epilepsy, as well as leveraging AI to understand experience of patients with Multiple Long-Term Conditions. He is also working on the development of grant proposals in AI- and ML-enabled applied health research, with a strong interest in fostering international collaborations between universities and healthcare organizations in the UK and internationally.
If you are interested in pursuing a collaboration or project in the fields of digital health, applied health studies, or eHealth, including:
Health Data Science: Leveraging advanced techniques in machine learning, deep learning, and big data to accelerate health research and improve healthcare services. This includes enhancing diagnostic accuracy, prediction capabilities, and treatment outcomes across various disease contexts such as cancers, infectious diseases, neurological disorders, eye conditions, and dentistry.
Research and Evaluation on AI Healthcare Applications: Investigating and assessing the applications of artificial intelligence in healthcare to drive innovation and optimize patient care and health management.
Please feel free to contact Hossein Ahmadi via email if you would like to discuss potential collaborations or have any questions.
About
Hossein Ahmadi earned his PhD in Information Systems in 2016 under a highly competitive Malaysian government scholarship. Since then, he has built extensive teaching and research experience across several prestigious institutions, including the °µÍø½âÃÜ, Aston University, Tehran University of Medical Sciences, and Iran University of Medical Sciences. He is currently a Research Fellow at the Centre for Health Technology, within the School of Nursing and Midwifery (SNAM), °µÍø½âÃÜ. Previously, he served as a Research Associate in the Operations and Information Management Department at Aston University (2020–2021) and as a Postdoctoral Fellow in the Health Information Management Department at Tehran University of Medical Sciences (2016–2018).
Hossein has over 10 years of research experience and has published more than 80 peer-reviewed journal articles. His research spans a wide range of clinical and care domains, including Parkinson’s disease, ophthalmic conditions, breast cancer, infectious diseases, hyperlipidaemia, hepatitis, mesothelioma, respiratory infections, and cardiovascular diseases. Across these areas, he has developed and applied novel artificial intelligence (AI) and machine-learning (ML) methods to enable accurate, reliable, and efficient disease diagnosis, prediction, and classification.
As a health data scientist, Hossein leads and contributes to applied health and digital health research, with a particular focus on health data science, machine learning, and big-data analytics to accelerate health research, enhance healthcare services, and improve diagnostic accuracy. At the °µÍø½âÃÜ Centre for Health Technology, he acts as both project lead and specialist contributor, providing expertise across projects involving patient experience analysis, cancer classification, mental health identification, EEG classification, disease segmentation and prediction, and diagnostic test evaluation.
The outcomes of his research have been published in leading international journals, including Biocybernetics and Biomedical Engineering, Journal of Affective Disorders, Telematics and Informatics, Journal of Medical Informatics, International Journal of Fuzzy Systems, Journal of Cleaner Production, Computers & Industrial Engineering, Universal Access in the Information Society, Technology in Society, Expert Systems with Applications, Technological Forecasting and Social Change, Computers in Human Behavior, Applied Soft Computing, Journal of Infection and Public Health, Computer Methods and Programs in Biomedicine, and MethodX, among others.
🔗 Google Scholar profile:
His interdisciplinary research demonstrates significant academic impact, with strong citation metrics reported by Google Scholar (6,205 citations; h-index: 38) and Scopus (3,311 citations; h-index: 29).
Hossein has developed strong links with various groups within the University and beyond. He mainly involved with the Data-lab project connected with NHS Kernow Clinical Commissioning Group (CCG), first working on a specific sub-project using machine learning to analyze large integrated data sets for NHS Kernow CCG, then continuing to work with the wider EPIC team on data science projects for promoting eHealth in the Cornwall region. He focused on how to promote awareness and develop new products and services in health data science, Internet of things, and other digital devices. Hossein works with a core team of academics from the Schools of Engineering, Computing and Mathematics and the SNAM, on work packages that support health and social care providers as well as SMEs in Cornwall. Hossein has led on journal publications in the related areas. He also helped to generate new ideas to continue the work through collaborative projects such as Generating Older Active Lives Digitally (ESRC funded) project.Ìý
Supervised Research Degrees
Supervisor of PhD Student
1. Machine learning-based prediction of endometrial cancer prognosis, Candidate name: Sherif Shazly (Co-Supervisor), 2024-recently completed.
SupervisorÌýÌýÌý ofÌýÌýÌý MasterÌýÌýÌý Students
- Evaluating the Effectiveness of Integrated Care Pathways for Older Adults with Complex Needs, Student name: Queendalin Ijeoma Uzoukwu (Co-Supervisor), 2025, active.
- Sentiments in social media: Gaining Insights into Patient Experiences with Mental Health and Long-Term Conditions by NLP Techniques, Student name: Bala Murugan Balaji (Co-Supervisor), 2025, active.
- Transforming Patient Narratives into Insights: Sentiment Analysis of Cancer Stories on Social Media Platform Using AI Techniques, Student name: Oluwabunmi Akintunde (Co-Supervisor), 2025, active.
- Sentiment Analysis of Children with Multiple Long-Term Conditions from Social Media, Student name: Temidayo Oluwalade (Co-Supervisor), 2024, completed.
- Sentiment analysis of patient from care opinion, Student name: Alexander Duruigbo (Co-Supervisor), 2024, completed.
- Developing a Personal Health Record System for Hypothyroid Patients, Student name: Roohparvar Esmaeili (Supervisor), 2018-2019, completed.
- Developing a Management Dashboard for Hospital Oncology Ward, Student name: Mahboobe Rezazadeh (Supervisor), 2018-2019, completed.
- Investigating the Effect of Sending Short Text Messages as Reminders on Medication Adherence in Patients with Chronic Hyperlipidemia: A Randomized Controlled Trial, Student name: Zeinab Mahdian (Supervisor), 2018-2019, completed.
- Factors Related to the Acceptance of Radio Frequency Identification Technology in Health Information Management Departments of Hospitals Affiliated to Iran University of Medical Sciences, Student name: Soghra Rostami Garavand (Co-Supervisor), 2017-2019, completed.
SupervisorÌýÌýÌý ofÌýÌýÌý UndergraduateÌýÌýÌýÌýÌýÌýÌýÌýÌý Students
- Explaining Students’ Use of Mobile Web 2.0 Learning: An Integrated Approach, Student name: Saleem Rahman (Supervisor), 2019-2020
- A Behavioral Intention Model for SaaS-based Collaboration Services, Student name: Mahad Gholam, (Supervisor), 2019-2020
- Face Detection using Python in the Context of Crime, Student name: Aland Siami, (Supervisor), 2019-2020
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Teaching
My teaching interests focused on the following areas:
- ÌýHealth Data Analytics
- ÌýMachine Learning and Artificial Intelligence for HealthcareÌý
- ÌýManagement Information Systems
- ÌýIntelligent SystemsÌý
Business Intelligence (BSc) 2016Ìý
Information Technology Management (BSc) 2016Ìý
Management Information Systems (MSc) 2017Ìý
Project Management for Information Systems (PhD) 2018
Security and Data Privacy (PhD) 2018Ìý
Computer Programming (python) (BSc) 2019Ìý
Intelligent Systems (BSc) 2019Ìý
Health Data Analysis (MSc) 2022; °µÍø½âÃÜ University, UK
Advanced Concepts in Research: Methodology and Methods (MSc) (22/AU/M) 2022 °µÍø½âÃÜ University, UK
Machine Learning and Artificial Intelligence for Healthcare (MSc) (22/AU/M) 2023 °µÍø½âÃÜ University, UK
Machine Learning and Artificial Intelligence for Health (MSc) (22/AU/M) 2024 °µÍø½âÃÜ University, UK
Machine Learning and Artificial Intelligence for Health (MSc) (22/AU/M) 2025 °µÍø½âÃÜ University, UK
Contact Hossein