Volume 1
Machine Learning Applications in Psychology: Enhancing Understanding and Interventions
Authors
Habibeh Nazarian
Abstract
The advent of Machine Learning (ML) within psychological research and mental health care marks a crucial paradigm shift, substantially enriching our understanding and treatment approaches for disorders like depression and anxiety. ML’s profound analytical prowess allows for the processing of a diverse array of data types, from behavioral metrics to environmental influences, thus deepening our comprehension of intricate psychological phenomena. These advancements enhance not only the accuracy of predictions but also enable the detection of critical patterns, which may facilitate the development of personalized therapeutic strategies. However, the integration of ML in this field is not without its challenges, including issues of data integrity, algorithmic bias, and model opacity. Moreover, the reliance on extensive, diverse datasets highlights the need for substantial data representation to support the empirical foundations of the discipline. This study underscores the transformative potential of ML in psychological research, setting the stage for future innovations that promise to advance the field further.
Keyword: Psychology, ML, Neuroimaging, Emotions, Disorders
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