E F Haghish
Position
Postdoctoral Fellow, Artificial Intelligence & Mental Health
Affiliation
- haghish@uib.no
- Visitor address
-
Christies gate 12
5015 Bergen - Room: 514
- Postal address
-
P.O. Box 7807NO-5020 BergenNorway
Follow me
E F Haghish
Position
Postdoctoral Fellow, Artificial Intelligence & Mental Health
Affiliation
Research groups
Short info
Research
I'm a postdoctoral researcher in Artificial Intelligence and Health Psychology. My work focuses on improving the transparency and robustness of AI models and adapting them for mental health research, particularly in the context of adolescent suicidality and self-destructive behavior. I'm currently validating the generalizability of the Theory of Adolescent Suicidality and Self-Destruction and exploring AI applications in data-driven theory development and assessment.
My statistical and AI research is hosted on GitHub: https://github.com/haghish
My recent psychological publications are on Researchgate: https://www.researchgate.net/profile/E-F-Haghish
Publications
2020
- Dominique Van Praag; Haghish Ebad Fardzadeh; Amra Covic et al. (2020). Preliminary validation of the Dutch version of the Posttraumatic stress disorder checklist for DSM-5 (PCL-5) after traumatic brain injury in a civilian population. (external link)
- Haghish Ebad Fardzadeh (2020). Developing, maintaining, and hosting Stata statistical software on GitHub. (external link)
- Ali Teymoori; A Gorbunova; Haghish Ebad Fardzadeh et al. (2020). Factorial Structure and Validity of Depression (PHQ-9) and Anxiety (GAD-7) Scales after Traumatic Brain Injury. (external link)
2023
- Haghish Ebad Fardzadeh; Milan Obaidi; Thea Bertnes Strømme et al. (2023). Mental Health, Well-Being, and Adolescent Extremism: A Machine Learning Study on Risk and Protective Factors. (external link)
- Haghish Ebad Fardzadeh; Nikolai Olavi Czajkowski (2023). Reconsidering False Positives in Machine Learning Binary Classification Models of Suicidal Behavior. (external link)
- Haghish Ebad Fardzadeh; Nikolai Olavi Czajkowski; Tilmann Martin von Soest (2023). Predicting suicide attempts among Norwegian adolescents without using suicide-related items: a machine learning approach. (external link)
- Haghish Ebad Fardzadeh; Ragnhild Bang Nes; Milan Obaidi et al. (2023). Unveiling Adolescent Suicidality: Holistic Analysis of Protective and Risk Factors Using Multiple Machine Learning Algorithms. (external link)
- Connor Spiech; Tor Endestad; Bruno Laeng et al. (2023). Beat alignment ability is associated with formal musical training not current music playing. (external link)
- Haghish Ebad Fardzadeh; Bruno Laeng; Nikolai Olavi Czajkowski (2023). Are false positives in suicide classification models a risk group? Evidence for “true alarms” in a population-representative longitudinal study of Norwegian adolescents. (external link)
2021
- Haghish Ebad Fardzadeh; Werner Vach; Anders Højen et al. (2021). Estimating measurement error in child language assessments administered by daycare educators in large scale intervention studies. (external link)
- Tilmann von Soest; Michal Kozák; Ruben Rodriguez Cano et al. (2021). Adolescents’ psychosocial well-being one year after the outbreak of the COVID-19 pandemic in Norway. (external link)
2024
- Haghish Ebad Fardzadeh; Juan Sahuquillo; Andreea Radoi et al. (2024). Validating the Spanish translation of the posttraumatic stress disorder checklist (PCL-5) in a sample of individuals with traumatic brain injury. (external link)
- Haghish Ebad Fardzadeh; Nikolai Olavi Czajkowski; Fredrik Andreas Walby et al. (2024). Suicide attempt risk predicts inconsistent self-reported suicide attempts: A machine learning approach using longitudinal data. (external link)
- Razieh Chegeni; Dominic Sagoe; Andre Syvertsen et al. (2024). Some for a Good Time, Some for a Long Time: Women’s Ratings of the Mate Value of Men with Different Addictions–An Experimental Study. (external link)
Projects
Child and Adolescent Self-Destructive Thoughts and Behavior: Conceptualizing and Holistic Risk Assessment