معرفی
Goran Nenadic is a Professor in the Department of Computer Science at the University of Manchester and a Turing Fellow at the Alan Turing Institute. His research focuses on natural language processing (NLP), text mining, and semi-automated knowledge curation from unstructured data, particularly in biomedical and healthcare domains. He leads the UK Healthcare Text Analytics Network (Healtex) and has extensive experience in clinical text mining, including projects with healthcare providers and industrial partners.
Education:
- PhD in Computer Science (2003, School of Sciences, University of Salford)
- MSc in Computer Science (1997, Faculty of Mathematics, University of Belgrade)
- BSc in Mathematics and Computer Science (1993, Faculty of Mathematics, University of Belgrade)
Research Interests: Nenadic's work emphasizes large-scale extraction of clinical/epidemiological findings from EHRs, healthcare social media, and biomedical literature. His team addresses challenges like medication prescription extraction, patient-generated data analysis, and clinical decision support systems. Projects include semi-automated anonymization of clinical narratives and mental health symptom identification in social media.
Key Projects:
- Integrating hospital outpatient letters into the healthcare data space (2021–2025)
- Centre for Digital Trust and Society (2021–present)
- SC-SVI: Social Care Strengths and Vulnerability Index (2022–2024)
- Assembling the Data Jigsaw for MSK Disease Research (2020–2024)
Labs/Teams: Leads the Clinical Knowledge Management group and collaborates with the Health eResearch Centre (HeRC). His group's website is gnteam.cs.manchester.ac.uk.
His research contributes to UN Sustainable Development Goals related to health and well-being through innovations in clinical text analytics and healthcare data utilization.
