Research Information System
Journal of Industrial and Systems Engineering, vol.16, no.2, pp.1-25, 2024 (Peer-Reviewed Journal)
One of the constant problems that people with mental health conditions
are faced with now is that they cannot establish a good relationship
with their therapist, or the client's disease type is not in the
therapist's specialty. These clients may not receive adequate treatment
and stop the therapy before feeling well. Therefore, the classification
of mental patients based on their disorder types and allocating a
therapist with the same expertise to them could lead to better treatment
and improve the quality of the therapy sessions. This paper will
compare several machine learning (ML) algorithms to classify patients
with mental conditions. Moreover, benefiting from the best ML algorithm,
patients will be categorized into different classes based on their
disorder types. Finally, a mathematical model will be developed to
determine the allocation policy of therapists to each group of patients
to maximize the summation of the utilization between therapists and
patients. To explore the implementation of the proposed method, we have
conducted a real-life case study to assess the validation of the model.