Self Reported Diary

Self-reported diaries, encompassing personal accounts of experiences and emotions, are increasingly integrated with objective data sources to improve various applications. Current research focuses on leveraging machine learning, particularly deep learning models like transformers and language models, to analyze diary entries alongside sensor data for tasks such as affect prediction and personalized health monitoring. This interdisciplinary approach holds significant promise for advancing personalized medicine, improving healthcare delivery (e.g., in intensive care), and facilitating the analysis of large-scale historical datasets. The development of robust methods for processing and interpreting diary data, including handling diverse languages and formats, remains a key challenge and area of active investigation.