Tardive Dyskinesia Development, Superoxide Dismutase Levels, and Relevant Genetic Polymorphisms commentary on manuscript focusing on prediction models

Critical Commentary       Strengths: Timely and Relevant: The review addresses a critical clinical problem (TD) by investigating the oxidative stress hypothesis, which remains a leading theory in the field. Integration of Levels: The manuscript successfully bridges the gap Read More …

Leveraging Machine Learning to Investigate the Link between Exposure to Major Air Pollutants and the Escalation of Suicide Rates in OECD Countries commentary on paper focusing on environment

Kadir Uludag’s study, “Leveraging Machine Learning to Investigate the Link between Exposure to Major Air Pollutants and the Escalation of Suicide Rates in OECD Countries” (2024), represents a timely and methodologically innovative contribution to the growing field of environmental psychiatry. Read More …

Antipsychotic-based machine learning models may help prediction of tardive dyskinesia in patients with schizophrenia (introductionary comment on manuscript)

A Calculated Risk: Commentary on “Antipsychotic-based machine learning models may help prediction of tardive dyskinesia in patients with schizophrenia” The advent of machine learning (ML) in psychiatry offers a tantalizing promise: to tame the inherent complexity and heterogeneity of mental Read More …

The relationship between complex PTSD and dissociation: longitudinal findings across Western and South Asian female samples commentary

Commentary: Advancing Our Understanding of the Complex Dance Between Dissociation and PTSD The intricate relationship between dissociation and post-traumatic stress has long been a subject of theoretical debate and clinical observation. The new study by Fung and colleagues, “The relationship Read More …