Persuasive Computing Lab

Check out our latest publication with Grace Ataguba (PhD), and Prof. Rita Orji, PhD

This chapter explores food and drug interactions, focusing on how foods and supplements react with drugs used to treat different health conditions. It reviews how machine learning (ML) algorithms are used to predict these interactions and support clinical decision-making. It also examines how much research has covered the pharmacokinetic impact of these interactions in empirical and ML-based studies. The main findings show that most interactions had a positive pharmacokinetic impact, while some were negative or inconclusive, and that deep neural networks achieved very high prediction accuracy.

You can read the full paper here: https://lnkd.in/dwdBHeKa

Dalhousie University, Dalhousie Computer Science

Check out our latest publication with Emeka Nwagu, Bilikis Banire, Grace Ataguba (PhD), Sandra Meier, Prof. Rita Orji, PhD

This review analyzes 46 peer-reviewed studies with 18,122 participants to uncover trends and identify gaps in problematic smartphone use (PSU) interventions. It evaluates interaction design strategies and their limitations in achieving sustained behavior change, considering the influence of intervention duration and user diversity. The review identifies key gaps and proposes eight research questions to advance the field. It offers a theoretical foundation and recommendations to improve the design, implementation, and evaluation of PSU interventions.

You can read the full paper here: https://lnkd.in/eqWr27sn

Dalhousie University, Dalhousie Computer Science