Nour Kanso
Contact details
Biography
PhD in Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King’s College London (2022-2026).
MRes in Cancer Biology (Informatics Stream), Department of Surgery and Cancer, Imperial College London (2021-2022).
BSc (Hons) in Biomedical Sciences, College of Health, Medicine and Life Sciences, Brunel University London (2018-2021).
Awarded a funded PhD studentship from the Centre for Doctoral Training in Data-Driven Health (KCL DRIVE-Health).
Research interests:
- Anxiety and depression
- NHS Talking Therapies
- Psychological treatment outcomes
- Longitudinal data
- Prediction modelling
My primary research interest lies in understanding mental health treatment outcomes for patients with anxiety and depressive disorders. My PhD project is focused on developing prediction models that identify individuals at risk of poor prognostic outcomes following psychological treatment using data collected by the NHS Talking Therapies service (previously known as IAPT). I am supervised by Prof Thalia Eley and Dr Ewan Carr.
Research groups:
- The Emotional Development, Interventions and Treatment (EDIT) Lab
Expertise and Public Engagement:
- DRIVE Health Symposium Organising Committee Member
Research
Emotional Development, Interventions and Treatment (EDIT) Lab
The EDIT lab studoes genetic and environmental influences on the development and treatment of anxiety and depression.
Statistical and Computational Genetics and Genomics (SCGG) RIG
The SCGG Group brings together researchers at King’s who are developing and working with innovative quantitative and computational approaches for genomic discovery and its impact on human health.
Research
Emotional Development, Interventions and Treatment (EDIT) Lab
The EDIT lab studoes genetic and environmental influences on the development and treatment of anxiety and depression.
Statistical and Computational Genetics and Genomics (SCGG) RIG
The SCGG Group brings together researchers at King’s who are developing and working with innovative quantitative and computational approaches for genomic discovery and its impact on human health.