Clinics to Algorithms Using Science and Technology

Abstract

The chapter addresses the persistent concerns surrounding the detecting and early intervention of anxiety and mood disorders. These mental health conditions have become increasingly prevalent, affecting individuals across various ages and socio-economic backgrounds. However, despite the growing awareness of their impact, challenges persist in timely diagnosis, leading to delayed treatment and aggravated conditions. By examining the continuum from clinical settings to algorithmic analyses, the chapter strives to elucidate how intelligent solutions, fueled by datasets, artificial intelligence (AI), machine learning (ML), and deep learning (DL), can enhance the accuracy, efficiency, and accessibility of diagnosis. The chapter's primary concern revolves around leveraging the power of science and technology to revolutionize the diagnostic landscape. It aims to unravel the transformative potential of transitioning from conventional clinical assessments to data-driven algorithms.