A Review on Deep Learning for Quality of Life Assessment Through the Use of Wearable Data.

ABSTRACT: Quality of Life (QoL) assessment has evolved over time, encompassing diverse aspects of human existence beyond just health. This paper presents a comprehensive review of the integration of Deep Learning (DL) techniques in QoL assessment, focusing on the analysis of wearable data. QoL, as defined by the World Health Organisation, encompasses physical, mental, and social well-being, making it a multifaceted concept. Traditional QoL assessment methods, often reliant on subjective reports or informal questioning, face challenges in quantification and standardization. To address these challenges, DL, a branch of machine learning inspired by the human brain, has emerged as a promising tool. DL models can analyze vast and complex datasets, including patient-reported outcomes, medical images, and

SUBMITTER: Skaramagkas V 

PROVIDER: S-EPMC11793860 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature